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REGULATION OF GENE EXPRESSION BY THE ANDROGEN RECEPTOR AND HEDGEHOG PATHWAYS IN BREAST CANCER CELLS
VIVIAN YAR LI CHUA
B.SC. (HONS)
THIS THESIS IS PRESENTED FOR THE DEGREE OF DOCTOR OF
PHILOSOPHY OF THE UNIVERSITY OF WESTERN AUSTRALIA, SEPTEMBER
2015
SCHOOL OF PATHOLOGY AND LABORATORY MEDICINE
UNIVERSITY OF WESTERN AUSTRALIA
PERTH, WESTERN AUSTRALIA
Declaration
The work detailed in this thesis was performed by the candidate unless otherwise
specified. This thesis is submitted for the degree of Doctor of Philosophy at the
University of Western Australia and has not been submitted elsewhere for any other
degree.
PhD Candidate:
Vivian Yar Li CHUA
Date:______________
Principal Supervisor:
Adjunct Associate Professor Jacqueline BENTEL
Date:______________
Coordinating Supervisor:
Winthrop Professor Jennet HARVEY
Date:______________
Co-supervisor:
Professor Bu YEAP
Date:______________
TABLE OF CONTENTS Acknowledgements ............................................................................................................. i Awards ............................................................................................................................... ii Publications ....................................................................................................................... iii List of Figures .................................................................................................................... v List of Tables................................................................................................................... viii Abbreviations .................................................................................................................... ix Abstract ............................................................................................................................ xv
CHAPTER 1: GENERAL INTRODUCTION
1.1 The Human Mammary Gland .................................................................................. 1
1.2 Breast Cancer ............................................................................................................. 2
1.2.1 Classification of Breast Cancer ........................................................................... 3
1.3 Breast Cancer Risk Factors....................................................................................... 5
1.4 Regulation of Breast Cancer Growth ....................................................................... 8
1.4.1 Oestrogen Receptor (ER) ................................................................................... 8
1.4.2 Progesterone Receptor (PR) .............................................................................. 10
1.4.3 Human Epidermal Growth Factor-Like Receptor 2 (HER2) ............................ 11
1.4.4 Androgens and the Androgen Receptor ............................................................ 12
1.4.4.1 Androgens ................................................................................................. 12
1.4.4.2 The Androgen Receptor ............................................................................ 13
1.4.4.3 Androgens and the AR in Breast Cancer .................................................. 15
1.4.4.4 Androgens and AR Modulators as Therapies for Breast Cancer ............. 17
1.4.5 The Hedgehog Signalling Pathway ................................................................... 18
1.4.5.1 Hedgehog Signalling in Breast Cancer ..................................................... 20
1.4.5.2 Crosstalk between the Hedgehog Signalling Pathway and Hormone
Receptors .............................................................................................................. 21
1.5 Breast Cancer Treatment ........................................................................................ 22
1.6 The ABC Transporters ............................................................................................ 24
1.6.1 The ABC Transporter Superfamily ................................................................... 25
1.6.2 Physiological Roles of the ABC Transporters .................................................. 26
1.6.3 ABC Transporters in Cancer ............................................................................. 27
1.6.3.1 ABCB1 / P-glycoprotein (P-gp) ............................................................... 28
1.6.3.2 ABCG2 / Breast Cancer Resistance Protein (BCRP) ............................... 31
1.6.3.2.1 ABCG2 in Breast Cancer ................................................................. 33
1.6.3.2.2 ABCG2 Protein Structure and Synthesis ......................................... 33
1.6.3.3 ABCC / Multidrug Resistance Protein (MRP) ......................................... 35
1.6.4 Modulators of the ABC Transporters ................................................................ 36
1.7 Epithelial-to-Mesenchymal Transition (EMT) ...................................................... 37
1.7.1 Physiological Processes Mediating EMT .......................................................... 38
1.7.1.1 Cell-to-Cell Adhesion Complexes ............................................................ 39
1.7.1.2 Integrin-Mediated Focal Adhesions.......................................................... 41
1.7.1.3 Matrix Metalloproteinases (MMPs) ......................................................... 42
1.7.2 Regulation of EMT by Signalling Pathways .................................................... 42
1.7.2.1 TGFβ Pathway .......................................................................................... 42
1.7.2.2 The WNT Signalling Pathway .................................................................. 44
1.7.2.3 The Notch Signalling Pathway ................................................................. 47
1.7.3 EMT in Breast Cancer ....................................................................................... 49
1.8 Statement of Aims .................................................................................................... 52
CHAPTER 2: MATERIALS
2.1 Reagents .................................................................................................................... 53
2.1.1 Cell Culture ....................................................................................................... 53
2.1.2 Immunofluorescence Microscopy ..................................................................... 53
2.1.3 Flow Cytometry and Cell Sorting ..................................................................... 54
2.1.4 Western Blotting ................................................................................................ 54
2.1.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing ................. 54
2.1.6 General .............................................................................................................. 55
2.2 Laboratory Equipment ............................................................................................ 56
2.2.1 Cell Culture ....................................................................................................... 56
2.2.2 Immunofluorescence Microscopy ..................................................................... 57
2.2.3 Flow Cytometry and Cell Sorting ..................................................................... 57
2.2.4 Western Blotting ................................................................................................ 58
2.2.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing ................. 58
2.2.6 General .............................................................................................................. 59
2.3 Antibodies ................................................................................................................. 60
2.4 Commercial Kits....................................................................................................... 61
2.5 Computer Programmes ........................................................................................... 62
CHAPTER 3: METHODS
3.1 Cell Culture .............................................................................................................. 63
3.1.1 Maintenance of Breast Cancer Cell Lines ......................................................... 63
3.1.2 Cryopreservation of Cell Lines ......................................................................... 63
3.1.3 Thawing of Cell Lines ....................................................................................... 63
3.1.4 Isolation of Breast Cancer Stem-Like Cells ...................................................... 64
3.1.5 Treatment of Breast Cancer Cell Lines ............................................................. 64
3.1.5.1 MTS Proliferation Assay ......................................................................... 64
3.1.5.2 Immunofluorescence Microscopy............................................................. 65
3.1.5.3 Flow Cytometry ........................................................................................ 65
3.1.5.4 Western Blotting ....................................................................................... 66
3.1.5.5 RNA Extraction ........................................................................................ 67
3.1.5.6 Wound Healing Assays ............................................................................. 67
3.1.5.7 Biocoat™ Matrigel™ Invasion Assays ....................................................... 68
3.1.5.8 3D Matrigel™ Colony Formation Assays .................................................. 68
3.2 MTS Proliferation Assays ....................................................................................... 69
3.3 Immunofluorescence Microscopy ........................................................................... 70
3.4 Flow Cytometry ........................................................................................................ 70
3.5 Fluorescence-Activated Cell Sorting (FACS) ........................................................ 71
3.6 Subcellular Fractionation ........................................................................................ 72
3.7 Western Blotting ...................................................................................................... 72
3.7.1 Whole Cell Lysis ............................................................................................... 72
3.7.2 SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE) .................................. 72
3.7.3 Immunoblotting ................................................................................................. 73
3.8 Polymerase Chain Reaction (PCR) and Reverse Transcription Quantitative
PCR (RT-qPCR) ............................................................................................................ 74
3.8.1 RNA Extraction ................................................................................................ 74
3.8.2 Reverse Transcription ........................................................................................ 75
3.8.2.1 cDNA Synthesis Using Superscript™ III .................................................. 75
3.8.2.2 Preparation of cDNA Using the RT2 First Strand cDNA Synthesis Kit .. 75
3.8.3 Purification of cDNA ......................................................................................... 76
3.8.4 Primer Design .................................................................................................... 76
3.8.5 Polymerase Chain Reaction (PCR) .................................................................... 76
3.8.6 Agarose Gel Electrophoresis ............................................................................. 77
3.8.7 Reverse Transcription-Quantitative PCR (RT-qPCR) ...................................... 77
3.8.8 PCR Arrays ....................................................................................................... 78
3.9 Sanger Sequencing ................................................................................................... 80
CHAPTER 4: DHT AND CYCLOPAMINE EFFECTS ON THE EXPRESSION
AND FUNCTION OF ABCG2 IN MCF-7 AND T-47D CELLS 4.1 Introduction .............................................................................................................. 82
4.2 Results ....................................................................................................................... 89
4.2.1 DHT and Cyclopamine Regulation of Gene Expression in Breast Cancer Cells ..
.................................................................................................................................... 89
4.2.2 DHT and Cyclopamine Regulation of ABCG2 mRNA Levels in MCF-7 Cells ...
.................................................................................................................................... 90
4.2.3 DHT and Cyclopamine Regulation of ABCG2 Protein Levels in MCF-7 Cells ..
.................................................................................................................................... 94
4.2.4 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated MCF-
7 Cells ......................................................................................................................... 95
4.2.5 DHT and Cyclopamine Effects on ABCG2 Protein Degradation ................... 102
4.2.6 DHT and Cyclopamine Regulation of ABCG2 Efflux Activity ..................... 121
4.2.6.1 DHT and Cyclopamine Effects on the Sensitivity of MCF-7 Cells to
Mitoxantrone ....................................................................................................... 131
4.2.7 Isolation of Breast Cancer Stem-Like Cells from MCF-7 Breast Cancer Cells ....
.................................................................................................................................. 134
4.2.7.1 DHT and Cyclopamine Effects on ABCG2 and AR Protein Levels in
Breast Cancer Stem-Like Cells ........................................................................... 136
4.2.7.2 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated
Breast Cancer Stem-Like Cells ........................................................................... 143
4.3 Discussion ................................................................................................................ 148
CHAPTER 5: DHT AND CYCLOPAMINE REGULATION OF EMT IN MCF-7
AND T-47D CELLS
5.1 Introduction ............................................................................................................ 158
5.2 Results ..................................................................................................................... 164
5.2.1 DHT and Cyclopamine Regulation of EMT-Associated Genes in Breast
Cancer Cells ............................................................................................................. 164
5.2.1.1 Effects of DHT and Cyclopamine on ECM Remodelling ...................... 176
5.2.1.2 DHT and Cyclopamine Regulation of the WNT and TGFβ Pathways .. 177
5.2.1.3 Classification of DHT and Cyclopamine-Specific Pathways ................ 178
5.2.2 DHT and Cyclopamine Effects on MCF-7 Cell Migration and Invasion ....... 186
5.3 Discussion ................................................................................................................ 191
CHAPTER 6: GENERAL DISCUSSION ...................................................... 198
Future Directions ......................................................................................................... 210
REFERENCES ............................................................................................................. 215
APPENDICES
1: Buffers and Solutions ................................................................................................. 264
2: Description of Genes Screened in the RT2 Profiler EMT PCR Array (PAHS-090Z) .....
........................................................................................................................................ 273
3: EMT PCR Array Amplification and Melt Curves ..................................................... 277
4: RT2 Profiler EMT PCR Array Fold Regulation Data (MCF-7) ................................. 279
5: RT2 Profiler EMT PCR Array Fold Regulation Data (T-47D) .................................. 283
6: Description of Genes Screened in the RT2 Profiler Breast Cancer PCR Array (PAHS-131A) ............................................................................................................................. 287
i
ACKNOWLEDGEMENTS First and foremost, I would like to thank my principal supervisor, Dr Jacqueline Bentel
for accepting me as a PhD student, giving me this chance to continue my studies during
which I was able to grow as a person/scientist and also for helping me to realise things
that I never imagined I could accomplish. Thank you for being patient with me and I
can only ever repay you by continuing to do what you’ve taught or improve from that. I
would also like to acknowledge Winthrop Professor Jennet Harvey and Professor Bu
Yeap for taking on the role as my co-supervisors and for supporting, listening and
encouraging me throughout the years.
To all past and present members of the Bentel/Thomas Lab, Dr Marc Thomas, Dr
Jasmine Tay, Dr Alison Louw, my first mentor: Ebony Rouse, Jamie Rodgers, Abbie
Creamer, Danika Hope, Erin Bolitho and Agata Sadowska, thank you very much for
your patience, guidance, advice and company throughout these years.
Here, I would also like to acknowledge Dr Archa Fox (Harry Perkins Institute for
Medical Research) for use of the Nikon Eclipse fluorescence microscope, Associate
Professor Richard Allcock (Lotterywest State Biomedical Facility Genomics) for use of
the Roche Light Cycler, Mike Epis/Professor Peter Leedman (Harry Perkins Institute
for Medical Research) for allowing me to use the liquid handling robotics, Associate
Professor Nathan Pavlos (UWA) for his input into the fluorescence microscopy images,
Rom Krueger (Royal Perth Hospital Flow Cytometry Unit), for his guidance in the use
of the flow cytometer, Irma Larma, for her time and help with the cell sorter and
Professor Paul Rigby and Alysia Buckley for their assistance with the Nikon A1
confocal microscope.
To my family, Dad, Mum and Chris, thank you for always supporting me and providing
me with laughter and love. My only wishes to you are to be healthy and to live happily.
ii
AWARDS 1. I was recipient of the Basic Science Encouragement Award for my oral presentation
titled, “Interactions between the Androgen Receptor and Hedgehog Signalling
Pathways in Breast Cancer Cells” at the Young Investigators’ Day held by the Royal
Perth Hospital Medical Research Foundation on 31st October 2012.
2. I was awarded the Silver Prize sponsored by City of Perth and EMBL Australia for
my oral presentation titled, “Crosstalk Between the Androgen Receptor (AR) and
Hedgehog Signalling Pathways in Breast Cancer Cells” at the Australian Society for
Medical Research (ASMR) on 5th June 2013.
3. I was awarded the Basic Science Encouragement Award for my oral presentation
titled, “Regulation of Gene Expression by the Androgen Receptor (AR) and
Hedgehog Signalling Pathways in Breast Cancer Cells” at the Young Investigators’
Day held by the Royal Perth Hospital Medical Research Foundation on 3rd
September 2014.
iii
PUBLICATIONS (CONFERENCE ABSTRACTS AND PRESENTATIONS)
1. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Interaction between Androgen Receptor and Hedgehog Signalling in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2012.
2. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Androgen Receptor and Hedgehog Signalling Interaction in Breast Cancer”, Combined Biological Sciences Meeting (CBSM), August 2012.
3. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Interactions between the Androgen Receptor and Hedgehog Signalling Pathways in Breast Cancer Cells”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, October 2012.
4. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Oral presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2013.
5. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2013.
6. Chua, V., Roehrig, K., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Biochemistry and Molecular Biology (ASBMB), September 2013.
7. Chua, V., Chong, C., Harvey, J. and Bentel, J. Oral presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Cancer Council WA, October 2013.
8. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of Gene Expression in Breast Cancer Cells by the Androgen Receptor (AR) and Hedgehog Signalling Pathways”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, October 2013.
9. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Crosstalk between the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, 6th Barossa National Conference, November 2013.
10. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2014.
11. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2014.
iv
12. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of Gene Expression by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Young Investigators’ Day, Royal Perth Hospital Medical Research Foundation, September 2014.
13. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of ABCG2 Expression and Function in Breast Cancer Cells”, National Breast Cancer Foundation Conference 2014, Sydney, Australia, September 2014.
14. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the Drug Efflux Transporter, ABCG2, by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, 15th IUBMB 24th FAOBMB-TSBMB Conference, Taipei, Taiwan, October 2014.
15. Chua, V., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the ABCG2 Drug Efflux Transporter in Breast Cancer Cells”, 2015 American Association for Cancer Research (AACR) Conference, Philadelphia, USA, April 2015.
16. Chua, V., Harvey, J. and Bentel, J. Oral presentation titled: “Regulation of the ABCG2 Drug Efflux Transporter in Breast Cancer Cells”, Australian Society for Medical Research (ASMR), June 2015.
17. Chua, V., Yeap, B., Harvey, J. and Bentel, J. Poster presentation titled: “Regulation of the Drug Efflux Transporter ABCG2 by the Androgen Receptor (AR) and Hedgehog Signalling Pathways in Breast Cancer Cells”, Combined Biological Sciences Meeting (CBSM), August 2015.
v
LIST OF FIGURES Figure Title Page
1.1 Anatomy of the human mammary gland in females 1
1.2 Schematic diagram of the mammary epithelium at puberty and during pregnancy 2
1.3 Classification of breast tumours 3
1.4 The androgen receptor signalling pathway 14
1.5 Correlation of AR expression in breast tumours and overall survival of patients 17
1.6 The Hedgehog signalling pathway 19
1.7 Structural domains of the ABC transporters 25
1.8 Efflux of chemotherapeutic agents by ABCB1, ABCC1, ABCC10 and ABCG2 29
1.9 Putative binding sites of transcription factors in the ABCB1 promoter 30
1.10 ABCG2/BCRP gene and protein map 31
1.11 Transcriptional regulation of ABCG2 31
1.12 Structural domains of the ABCG2 half-transporter 34
1.13 Post-translational modification and plasma membrane trafficking of ABCG2 35
1.14 Epithelial-to-mesenchymal transition (EMT) 39
1.15 Adhesion complexes between adjacent cells and the ECM 40
1.16 TGFβ signalling 44
1.17 The canonical WNT signalling pathway 45
1.18 The non-canonical WNT/planar cell polarity (PCP) pathway 46
1.19 The non-canonical WNT/Ca2+ pathway 47
1.20 The Notch signalling pathway 48
3.1 Layout of the RT2 Profiler Human EMT PCR Array (PAHS-090Z) 79
3.2 Loading of 384-well RT2 Profiler PCR Arrays (G Format) 80
4.1 DHT and cyclopamine effects on cell proliferation and expression of breast cancer-associated genes 91
4.2 Optimisation of ABCG2 qPCR conditions 96
4.3 ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 cells 98
4.4 DHT and cyclopamine regulation of ABCG2 protein levels 99
4.5 Optimisation of primary and secondary antibody concentrations for investigation of ABCG2 intracellular localisation by immunofluorescence microscopy
103
vi
4.6 Intracellular localisation of ABCG2 in MCF-7 cells 105
4.7 Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in MCF-7 cells 106
4.8 Optimisation of experimental conditions for treatment of MCF-7 cells with the proteasome inhibitor, MG132 111
4.9 MG132 effects on the regulation of ABCG2 protein in DHT and cyclopamine treated MCF-7 cells 113
4.10 Treatment of MCF-7 cells with the lysosome inhibitor, chloroquine 115
4.11 Effects of lysosomal inhibition on DHT and cyclopamine induced regulation of ABCG2 protein levels 117
4.12 Intracellular co-localisation of ABCG2 and lysosomes 119
4.13 ABCG2 exon 12 cDNA sequence in MCF-7 cells 123
4.14 Flow cytometric analysis of the intracellular levels of ABCG2 substrates, mitoxantrone (MX) and Rhodamine 123 (Rhd123) in MCF-7 cells
124
4.15 Efflux of Rhodamine 123 from MCF-7 cells 126
4.16 Optimisation of mitoxantrone concentration for investigation of ABCG2 efflux activity 128
4.17 DHT and cyclopamine effects on the efflux rate of mitoxantrone from MCF-7 cells 130
4.18 Standard curve for MTS proliferation assays 132
4.19 Sensitivity of MCF-7 cells to mitoxantrone following treatment with DHT and cyclopamine 133
4.20 Optimisation of Hoechst 33342 concentration for flow cytometry 137
4.21 Optimisation of CD44-APC and CD24-BV421 antibodies for flow cytometry 138
4.22 Isolation of breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) from MCF-7 cells 140
4.23 Confirmation of stem cell properties in the breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) 141
4.24 DHT and cyclopamine regulation of ABCG2 and AR protein levels in breast cancer stem-like cells isolated from MCF-7 cultures 145
4.25 Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in breast cancer stem-like cells isolated from MCF-7 cultures 146
5.1 Efficiency curves for AR and GAPDH qPCR in MCF-7 and T-47D cells 167
5.2 DHT and cyclopamine regulation of AR mRNA levels 169
5.3 DHT and cyclopamine regulation of EMT-associated genes in MCF-7 cells 170
5.4 DHT and cyclopamine regulation of EMT-associated genes in T-47D cells 172
vii
5.5 Classification of DHT and cycopamine regulated EMT-associated genes in MCF-7 and T-47D cells 179
5.6 Mapping of DHT and cyclopamine regulated EMT-associated genes in MCF-7 cells to canonical pathways 181
5.7 Mapping of DHT and cyclopamine regulated EMT-associated genes in T-47D cells to canonical pathways 183
5.8 Pathways associated with genes regulated by ≥1.5-fold following DHT and cyclopamine treatments of MCF-7 and T-47D cells 185
5.9 DHT and cyclopamine effects on MCF-7 cell migration 188
5.10 DHT and cyclopamine regulation of MCF-7 cell invasion 189
viii
LIST OF TABLES
Table Title Page
1.1 The seven subfamilies/subclasses of the ATP-binding cassette (ABC) superfamily 26
3.1 Antibody dilutions for immunoblotting 74
3.2 Primers for PCR and RT-qPCR 78
4.1 Regulation of ABCB1 and ABCG2 mRNA levels in MCF-7 and T-47D cells 93
5.1 Pathway enrichment associated with DHT and cyclopamine regulated genes in MCF-7 cells 174
5.2 Pathway enrichment associated with DHT and cyclopamine regulated genes in T-47D cells 175
ix
ABBREVIATIONS α Alpha
β Beta
γ Gamma
µ Micro
ºC Degrees celsius
2-ME 2-Mercaptoethanol
3D 3-Dimensional
7-AAD 7-Aminoactinomycin D
ABC ATP-binding cassette
ADH Atypical ductal hyperplasia
AJ Adherens junctions
ALDH Aldehyde dehydrogenase
ALH Atypical lobular hyperplasia
AP1 Activator protein 1
APC Adenomatous polyposis coli
AR Androgen receptor
ARE Androgen response element
BAD BCL2-associated death promoter 2
BCL2 B-cell lymphoma 2
BMP Bone morphogenetic protein
BRCA Breast cancer susceptibility gene
BSA Bovine serum albumin
β-TrCP Beta-transducin repeat containing protein
CAMK2 Calcium/calmodulin-dependent kinase 2
CDK Cyclin-dependent kinase
cDNA Complementary DNA
ChIP Chromatin immunoprecipitation
CK1 Casein kinase 1
x
CO2 Carbon dioxide
CSCs Cancer stem cells
CSS Charcoal-treated foetal calf serum
Ct Threshold cycle
DAAM1 Disheveled-associated activator of morphogenesis 1
DBD DNA-binding domain
DCIS Ductal carcinoma in situ
DHEA Dehydroepiandrosterone
DHEA-S Sulphate-conjugated dehydroepiandrosterone
DHT 5α-Dihydrotestosterone
DMSO Dimethyl sulfoxide
DNA Deoxyribonucleic acid
DSH Dishevelled
E2 17β-Oestradiol
ECL Enhanced chemiluminescence
ECM Extracellular matrix
EDTA Ethylenediaminetetraacetic acid
EGF Epidermal growth factor
EGFR Epidermal growth factor receptor
EMT Epithelial-to-mesenchymal transition
ER Oestrogen receptor
ERE Oestrogen response element
ERK Extracellular signal-regulated kinase
ERM Ezrin-radixin-moesin
EV Extracellular vesicle
F-actin Filamentous actin
FAK Focal adhesion kinase
FCS Foetal calf serum
FEA Flat epithelial atypia
xi
FGF Fibroblast growth factor
FN1 Fibronectin
FSC Forward scatter
FTC Fumitremorgin C
5-FU 5-Fluorouracil
FZD Frizzled
g Gram
GAPDH Glyceraldehyde-3-phosphate dehydrogenase
GLI Glioma-associated oncogene
GSK3β Glycogen synthase kinase 3β
GTF General transcription factors
h Hour
HAT Histone acetyltransferase
HDAC Histone deacetylase
HER2 Human epidermal growth factor-like receptor 2
HGF Hepatocyte growth factor
HRT Hormone replacement therapy
HSP Heat shock protein
IDC Invasive ductal carcinoma
IGF Insulin-like growth factor
IGFR Insulin-like growth factor receptor
JAM Junction adhesion molecule
JNK c-Jun N-terminal kinase
kDa Kilodalton
KLK Kallikrein
KRT Keratin/cytokeratin
L Litre
LBD Ligand-binding domain
LCIS Lobular carcinoma in situ
xii
LLC Large latency complex
LRP Lipoprotein receptor-related protein
M Molar
MAPK Mitogen-activated protein kinase
MCF-7 Michigan Cancer Foundation-7
MDR Multidrug resistance
MET Mesenchymal-to-epithelial transition
MFI Mean fluorescence intensity
MgCl2 Magnesium chloride
miRNA MicroRNA
MMP Matrix metalloproteinase
mRNA Messenger RNA
MRP Multidrug resistance-associated protein
MSD Membrane spanning domain
MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulphophenyl)-2H-tetrazolium)
MX Mitoxantrone
MXR Mitoxantrone resistance
n Nano
NDB Nuclear-binding domain
NES Nuclear export signal
NFκB Nuclear factor kappa B
NLS Nuclear localisation signal
NTD N-terminal domain
P4 Progesterone
PAI-1 Plasminogen activator inhibitor 1
PBS Phosphate buffered saline
PCP Planar cell polarity
PCR Polymerase chain reaction
PFS Progression-free survival
xiii
P-gp P-glycoprotein
PI3K Phosphoinositide 3-kinase
PKA Protein kinase A
PKB Protein kinase B
PKC Protein kinase C
PMSF Phenylmethanesulfonyl fluoride
PR Progesterone Receptor
PRE Progesterone response element
PS Penicillin/streptomycin
PTCH1 Patched homologue 1
R2 Correlation coefficient
RhoA Ras homologue gene family, member A
Rhd123 Rhodamine 123
RNA Ribonucleic acid
RNAPolII RNA polymerase 2
rpm Revolutions per minute
RTK Receptor tyrosine kinase
RT-qPCR Reverse transcription quantitative PCR
SAPK Stress-activated protein kinase
SARM Selective androgen receptor modulator
SDS-PAGE SDS-polyacrylamide gel electrophoresis
S.E.M. Standard error of the mean
SERM Selective oestrogen receptor modulator
SHH Sonic hedgehog
SMO Smoothened
SNAI1 Snail1
SNAI2 Snail2 or Slug
SP Side population
SRC Src kinase
SSC Side scatter
xiv
TBP TATA-binding protein
TBS Tris-buffered saline
TCF/LEF T-cell factor/lymphoid enhancer factor
TGF-β Transforming growth factor beta
TJ Tight junction
TKI Tyrosine kinase inhibitor
TMD Transmembrane domain
TNBC Triple-negative breast cancer
TNFα Tumour necrosis factor alpha
U Unit
UV Ultraviolet
VEGF Vascular endothelial growth factor
VIM Vimentin
ZO-1 Zona occludens 1
xv
ABSTRACT The androgen receptor (AR) is expressed in 70-90% of breast tumours and its increased
expression in oestrogen receptor (ER) expressing breast cancers is correlated with better
disease prognosis and longer relapse-free and overall survival. The Hedgehog signalling
pathway has also been implicated in breast cancer growth, with Hedgehog signalling
intermediates and Hedgehog-induced target genes overexpressed in both early stage and
aggressive breast tumours. The androgen, 5α-dihydrotestosterone (DHT) and the
Hedgehog pathway inhibitor, cyclopamine, inhibit proliferation of the MCF-7 and T-
47D breast cancer cell lines and this thesis has investigated genes and cellular processes
regulated by these agents that would potentially impede breast tumour progression. In
DHT and cyclopamine treated MCF-7 and T-47D cells, screening of gene expression
using RT2 Profiler Human Breast Cancer PCR Arrays identified decreased expression of
both the ABC transporters, ABCB1 and ABCG2, which facilitate the development of
drug resistance in cancer cells, and regulators of epithelial-to-mesenchymal transition
(EMT), a program associated with induction of cancer cell motility, invasiveness and
metastasis.
PCR array results were further investigated in MCF-7 cells by RT-qPCR, which
identified that 24 h of treatment with 10-8 M DHT and the combination of 10-8 M DHT
and 2 µM cyclopamine reduced ABCG2 levels by 30-35%, while cyclopamine alone
had little effects on ABCG2 mRNA levels. During 8 days of treatment with DHT or
DHT and cyclopamine, ABCG2 protein levels were progressively decreased, with the
levels more rapidly reduced in cultures co-treated with both DHT and cyclopamine.
Using immunofluorescence microscopy, ABCG2 protein was found to accumulate in
cell-to-cell junction complexes as well as in large cytoplasmic, aggresome-like vesicles,
both of which were diminished following treatment of MCF-7 cells for 4 days with
DHT or DHT and cyclopamine. Interestingly, cyclopamine, which also decreased
ABCG2-associated cell-to-cell junction complexes, induced ABCG2 accumulation into
the aggresome-like vesicles. As ABC transporters including ABCG2 are functionally
active when bound to the membrane surface, these findings indicated that DHT and
cyclopamine treatments inhibited ABCG2 efflux activity. In support of this hypothesis,
DHT, cyclopamine and DHT/cyclopamine treatment of MCF-7 cells delayed the efflux
of mitoxantrone, an ABCG2 substrate and chemotherapeutic agent. Correspondingly,
xvi
the IC50 of mitoxantrone was reduced by ~70% (p<0.05) in cyclopamine and
DHT/cyclopamine treated MCF-7 cells. In breast cancer stem-like cells derived from
the MCF-7 cell line, DHT alone and the combination of DHT and cyclopamine reduced
ABCG2 protein levels by 35-45% after 8 days, a result comparable to that observed in
parental MCF-7 cells. Cyclopamine, which decreased ABCG2 protein levels by ~10%,
induced ABCG2 accumulation into aggresome-like vesicles whereas DHT and
DHT/cyclopamine treatments decreased the levels of ABCG2 in both cell-to-cell
junction complexes and in aggresome-like vesicles.
DHT and cyclopamine regulation of EMT-associated genes was investigated in MCF-7
and T-47D cells using RT2 Profiler Human EMT PCR Arrays. These studies identified
that DHT, cyclopamine and DHT/cyclopamine treatments of MCF-7 and T-47D cells
downregulated expression of mesenchymal markers, including SNAI1, TWIST1 and
vimentin but upregulated expression of the epithelial marker, KRT19, that encodes
cytokeratin-19. Pathway analysis of regulated genes using REACTOME identified that
the treatments predominantly downregulated expression of genes encoding components
of extracellular matrix (ECM) remodelling and cell-to-ECM interactions (e.g. collagens,
(COL1A2 and COL5A2), SPARC, versican (VCAN), fibronectin (FN1), integrins (ITGA5
and ITGB1)) as well as intermediates of pro-EMT signalling cascades, WNT (WNT5B,
CTNNB1, FZD7) and TGFβ (TGFB1, SMAD2, SERPINE1). Collectively, these findings
suggested inhibition or reversal of EMT and in support of these results, DHT,
cyclopamine and DHT/cyclopamine treatments of MCF-7 cells were found to inhibit
cell migration determined by wound healing assays and cell invasion in 3D Matrigel™
colony formation assays.
Development of drug resistance and tumour metastasis are major causes of breast
cancer-associated morbidity and mortality. Results from this study provide evidence
that androgens and Hedgehog signalling inhibitors may delay emergence of drug
resistant and metastatic disease by decreasing the expression and function of the
ABCG2 drug efflux transporter and inhibiting EMT.
Chapter 1
General Introduction
Chapter 1: General Introduction
1
1.1 The Human Mammary Gland
Humans have two mammary glands or breasts on the anterior chest wall and in women,
each mammary gland consists of a ductal-lobular system which produces milk as a
source of nourishment and nutrients for the young offspring (Figure 1.1) (Ali and
Coombes 2002). At birth, the mammary gland develops as a rudimentary tree-like
structure of ducts converging to a primitive nipple and during puberty and pregnancy,
the mammary glands of females but not males undergo dynamic changes (Ali and
Coombes 2002).
Figure 1.1: Anatomy of the human mammary gland in females. The female mammary gland is a source of nutrition for the offspring, producing milk in each alveolus which drains into the extensive branches of primary and secondary ducts that converge at the nipple. The ductal-lobular structure is surrounded by components of the stroma and expands into the mammary fat pad during puberty and pregnancy (Ali and Coombes 2002).
Growth of the female mammary gland is slow from birth to puberty but at the onset of
puberty, in response to regulators such as hormones secreted from the pituitary gland
(e.g. prolactin, growth hormone (GH)) and the ovaries (oestrogen, progesterone) and
growth factors (e.g. insulin-like growth factor (IGF)), cap cells at the tips of ducts
(terminal end buds (TEBs)) begin to proliferate rapidly, resulting in the formation of
secondary branches of ducts and invasion of the ducts into the mammary fat pad (Figure
1.2) (Topper and Freeman 1980, Ruan and Kleinberg 1999, Gallego et al 2001). During
pregnancy, hormones especially prolactin and progesterone stimulate further
proliferation and differentiation of cells to develop alveoli at the ends of ducts which
also undergo extensive branching and invasion to fill the entire mammary fat pad
(Naylor et al 2003). An alveolus is comprised of a single layer of polarised, milk-
producing alveolar epithelial cells which envelop a circular lumen connected to the
Chapter 1: General Introduction
2
primary ductal network (Figure 1.2) (Macias and Hinck 2012). A contractile layer of
myoepithelial cells lining the outer surface of alveolar cells and ducts facilitates
transport of milk towards the nipple. At weaning, when production of milk ceases, the
mammary epithelium undergoes involution, remodelling its architecture into a pre-
pregnancy structure, a process that involves degradation of cells via programmed cell
death or apoptosis (Marti et al 2001).
Figure 1.2: Schematic diagram of the mammary epithelium at (A) puberty and (B) during pregnancy. (A) Terminal end buds (TEBs) of mammary glands contain cap cells at the ends of ducts which undergo rapid proliferation, resulting in extension of the ductal structure into the mammary fat pad. (B) During pregnancy, further proliferation and differentiation of cells and branching of ducts lead to formation of alveoli, in which milk that is secreted by the alveolar epithelial cells, is drained into the ducts towards the nipple by the contractile activity of myoepithelial cells that surround the alveolar and ductal structures (Gajewska et al 2013).
1.2 Breast Cancer
Breast cancer predominantly affects women and, with ~1.7 million cases recorded in
2012, is the most frequently diagnosed cancer of females worldwide (Torre et al 2015).
The disease is also a leading cause of cancer-related death and accounts for ~15% of
cancer-related death of women (>500,000 cases in 2012), with half of these cases
reported in economically developed countries (Torre et al 2015). The prevalence of
breast cancer is proportionally higher in developed countries such as North America,
Australia, New Zealand and in northern and western European countries compared to
African and Asian countries, and this is at least in part due to differences in exposure to
breast cancer risk factors (Section 1.3) and availability of facilities for early breast
tumour detection in developed countries (Torre et al 2015). In Australia, breast cancer is
Chapter 1: General Introduction
3
the most prevalent cancer of women and is the second leading cause of cancer-related
death of women following lung cancer. In 2014, 15,270 breast cancer cases and 3000
deaths were reported (AIHW 2014). The average age at first diagnosis is 60.7 years and
1 in 11 women are at risk of developing breast cancer by the age of 75 (AIHW 2014).
1.2.1 Classification of Breast Cancer
Breast cancer is a clinically heterogeneous and progressive disease that can present at
various stages with differing severity, metastatic potential and disease prognosis. Breast
tumours can be classified according to histological or molecular features, which are
used to determine disease prognosis and to select appropriate therapies (Section 1.5).
The two broad classes of breast cancer are the in situ or the more clinically aggressive
invasive (infiltrating) carcinomas (Figure 1.3).
Figure 1.3: Classification of breast tumours. Breast cancer is broadly classified into in situ or invasive (infiltrating) carcinomas. In situ carcinoma of ductal origin (ductal carcinoma in situ (DCIS)) is more common than lobular carcinoma in situ (LCIS) and can be subclassified into comedo, cribiform, micropapillary, papillary and solid forms. The different types of invasive carcinomas include tubular, ductal lobular, invasive lobular, infiltrating ductal, mucinous, medullary and infiltrating ductal tumours (Malhotra et al 2010).
The major subtypes of breast cancers are classified as ductal or lobular in origin and the
majority of cases are observed to have progressed from abnormal precursor or pre-
invasive lesions (Bombonati and Sgroi 2011). For example, flat epithelial atypia (FEA)
Chapter 1: General Introduction
4
progresses into atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS),
which are precursors of invasive ductal carcinoma (IDC), that accounts for 40-75% of
breast cancers. Similarly, invasive lobular carcinoma, which represents a smaller
proportion of breast cancers (5-15%) is predicted to originate mainly from precursors,
atypical lobular hyperplasia (ALH) and lobular carcinoma in situ (LCIS) (Wellings and
Jensen 1973, Oyama et al 2000). Histological testing is important for the classification
of breast cancers, however it is well established that individual breast cancer cases with
the same classification and the same stage may have different responses to treatments
and different outcomes. Genetic-based techniques such as comparative genomic
hybridisation (CGH) were originally shown to differentiate low-grade IDC cases, which
exhibited chromosomal losses in 16q and gains in 1q, 16p and 8q, from higher grade
IDC, which was characterised by chromosomal losses in 8p, 11q, 13q, 1p, 18q, gains in
8q, 17q, 20q and 16p as well as frequent high-level amplification of 17q12 and 11q13
(Roylance et al 2006).
Molecular classification of breast tumours using high-throughput gene expression
profiling assays (e.g. DNA microarrays) and unbiased hierarchical clustering led to
identification of 6 major subclasses of breast cancers; luminal A, luminal B, human
epidermal growth factor-like receptor 2 (HER2)-overexpressing, basal-like, claudin-
low, and normal-like breast tumours (Perou et al 1999, Sorlie et al 2001, Sorlie et al
2003, Prat et al 2010). The luminal subtypes of breast tumours, which express oestrogen
(ER) and progesterone (PR) receptors, are associated with better disease prognosis and
contain chromosomal deletions in 16q and gains in 1q, a genetic alteration profile that is
rare in ER-ve breast cancers such as the HER2-overexpressing and basal-like breast
tumour subtypes (Ciriello et al 2013). Luminal A breast cancers are associated with
longer overall survival compared to luminal B and were also shown to express high
levels of ERα, cytokeratins 8 (KRT8) and 18 (KRT18), GATA-binding protein 3
(GATA3), X-box binding protein 1, trefoil factor 3 and the oestrogen-regulated gene,
LIV-1 (Ciriello et al 2013).
In comparison to the luminal subtypes, HER2-overexpressing and basal-like breast
cancers are characterised by higher grade tumours with poorer relapse-free and overall
survival of patients (Sorlie et al 2001). In HER2-overexpressing breast cancers, genes in
the HER2 amplicon at chromosome position 17q22-24, which include HER2 and
Chapter 1: General Introduction
5
growth factor receptor-bound protein 7 (GRB7), are amplified (Radhakrishna 2014).
The basal-like breast cancers share multiple genetic similarities with triple-negative
breast cancers, which lack expression of the hormone receptors, ER and PR as well as
HER2 (ER-ve/PR-ve/HER2-ve) (Sorlie et al 2001, Reis-Filho and Tutt 2008). However,
these subtypes of breast tumours are not entirely synonymous and this is supported by
findings which demonstrated five distinct TNBC subtypes, including two basal-like,
immunomodulatory, mesenchymal, mesenchymal stem-like and luminal androgen
receptor (LAR) subtypes (Lehmann et al 2011).
Claudin-low breast tumours are also ER-ve, PR-ve and HER2-ve and are associated
with poorer prognosis compared to the luminal subtypes. In line with this, claudin-low
breast cancers lack expression of the luminal differentiation markers (KRT18, KRT19,
oestrogen receptor 1 gene (ESR1), GATA3) but overexpress the epithelial-to-
mesenchymal transition (EMT) marker, vimentin and the EMT-associated transcription
factor, ZEB2 (Prat et al 2010). The normal breast-like breast cancers are less
reproducibly defined but have been associated with high histological grade of tumours,
expression of basal-like markers and low levels of expression of luminal genes (Sorlie
et al 2001). An alternative form of breast cancer classification has been demonstrated
previously which classified breast cancers according to expression of the androgen
receptor (AR). The three subtypes were ER alpha (ERα)+ve/AR+ve tumours which
correspond to luminal breast cancers, ERα-ve/AR-ve tumours, which include basal-like
breast cancers, and molecular apocrine ERα-ve/AR+ve breast cancers (Farmer et al
2005). The prognosis of these subtypes differ, with the ER+ve/AR+ve breast tumours
correlating with better prognosis of the disease compared to the ER-nonexpressing
AR+ve breast tumours (Section 1.4.4.3).
1.3 Breast Cancer Risk Factors
Breast cancer is a multifactorial disease, with endocrine, diet and lifestyle factors
proposed to increase lifetime risks for disease development. In a small proportion of
cases where familial clustering indicates genetic predisposition, several high penetrance
and a growing number of low penetrance genes have been identified and characterised
(Chen and Parmigiani 2007, Easton et al 2007, Apostolou and Fostira 2013). Lifetime
exposure of the mammary gland to ovarian hormones including oestrogen and
Chapter 1: General Introduction
6
progesterone may increase breast cancer risk. During menarche, increased oestrogen
levels in the mammary glands stimulate the extension of mammary ducts as well as
rapid proliferation of mammary cells that remain undifferentiated until pregnancy and
lactation, during which cells fully differentiate (Bodicoat et al 2014). The presence of
undifferentiated cells in the mammary glands is proposed to increase the risk of
developing harmful mutations during DNA replication and therefore women who had
experienced early menarche, late pregnancy or late onset of menopause are at higher
risks of developing breast cancer (Bodicoat et al 2014). In support of this hypothesis,
women with irregular cycles of menstruation were shown to be less likely to develop
breast cancer due to decreased (life) time in the luteal phase of the menstrual cycle,
during which secretion of ovarian hormones is highest (Terry et al 2005). Additionally,
hormone replacement therapies (HRT) using oestrogens and/or progestins to relieve
menopausal symptoms or prevent osteoporosis have also been associated with increased
risk of breast cancer development (Rossouw et al 2002).
Diet, including consumption of alcohol and a sedentary lifestyle also contributes to the
development of breast cancer. Moderate consumption of alcohol (5-9.9g/day or 3-6
glasses of wine/week) has been associated with an increased risk of developing breast
cancer, and an additional 10g of alcohol per day further increases the risk by ~10%
(Chen et al 2011b). Alcohol consumption predominantly affects the breast cancer risk
of postmenopausal women and is usually associated with ER+ve/PR+ve breast cancers
(Suzuki et al 2005). High consumption of alcohol has been linked to increased
circulating levels of oestrogen and aromatase, the enzyme which converts androgen
precursors into oestrogens, and these findings support the involvement of oestrogens
and the ER signalling pathway in the development of breast cancer associated with
alcohol consumption (Purohit 2000). Carcinogenic bi-products linked to high alcohol
consumption such as reactive oxygen radicals, lipid peroxides and acetaldehyde
following metabolism of alcohol may also increase breast cancer risk (Meagher et al
1999).
High fat diets and low physical activity leading to high body mass index (BMI) also
increase breast cancer risk, especially in postmenopausal women, where production of
oestrogens is predominantly due to peripheral conversion of androgen precursors by
aromatase. Adipose tissues produce aromatase and it is proposed that postmenopausal
Chapter 1: General Introduction
7
oestrogen production is higher in obese women, increasing the risk of developing breast
cancer (Liu et al 2013). In addition, buildup of fat in the abdomen and increasing BMI
have been associated with hyperinsulinemia and increased expression of insulin-like
growth factor 1 receptor (IGF1R) and IGF2, respectively. Together, these may stimulate
proliferation of mammary cells and increase the risk of breast cancer development
(Suga et al 2001).
The risk of developing breast cancer increases with the number of diagnoses in the
family, in particular first and second degree relatives or if relatives are diagnosed at a
younger age. Patients with breast cancers arising from hereditary genetic factors
(familial breast cancer) account for 5-7% of breast cancer cases and the most prevalent
cause of familial breast cancers, constituting ~25% of these cases is attributed to
germline mutation in one of the two breast cancer susceptibility genes, BRCA1 and
BRCA2 (Bradbury and Olopade 2007, Walsh et al 2010). Proteins encoded by BRCA1
and BRCA2 are involved in maintaining chromosomal stability, protecting the DNA
from damage, and repair of double-strand DNA breaks (Wu et al 2010). In individuals
carrying a mutation in BRCA1 or BRCA2, the estimated lifetime risk for breast cancer
development is 40-85% (Chen and Parmigiani 2007). Carriers of BRCA1 mutation also
have an elevated lifetime risk of 25-65% for development of ovarian cancer, while the
estimated lifetime risk for developing ovarian cancers in BRCA2 mutation carriers is 15-
20% (Chen and Parmigiani 2007).
A number of high penetrance but low frequency genes has also been identified which
when mutated in the germline, predispose to cancer, including breast cancer
development. These include TP53 and the phosphatase and tensin homologue gene
(PTEN), germline mutations of which cause the autosomal dominant inherited
disorders, Li Fraumeni syndrome and Cowden syndrome, respectively. TP53 mutation
carriers face a 90% estimated risk of developing cancers, with early onset breast cancer
(diagnosed before the age of 45) being the most common malignancy (Nichols et al
2001, Walsh et al 2006). Patients with Cowden syndrome have an estimated risk of 20-
50% for development of malignant breast cancer and 67% for development of benign
breast disease (Ngeow et al 2014). Other breast cancer susceptibility genes with
moderate penetrance include the gene encoding checkpoint kinase 2, CHEK2, and the
partner and localiser of BRCA2, PALB2, while the low penetrance and less common
Chapter 1: General Introduction
8
breast cancer predisposing genes such as mitogen-activated protein kinase kinase kinase
1 (MAP3K1) and fibroblast growth factor receptor 2 (FGFR2) only slightly increase the
risk for breast cancer development (Easton et al 2007, Hunter et al 2007, Rahman et al
2007, Stracker et al 2009).
1.4 Regulation of Breast Cancer Growth
ER, PR and HER2 regulate breast cancer growth and progression, and are used as
markers of breast tumour classification and to predict responses to endocrine or targeted
therapies. The epidermal growth factor receptor (EGFR), androgen receptor (AR) and
embryogenic/developmental (e.g. Hedgehog) pathways also regulate breast tumour
growth, however their role in breast cancer formation or progression are less well
defined.
1.4.1 Oestrogen Receptor (ER)
The ER, a member of the nuclear receptor superfamily is expressed in 70-80% of breast
cancers (Allred et al 2009). Two ER isoforms, ERα and ERβ, mediate the effects of
oestrogens (e.g. 17β-oestradiol (E2)) and are encoded by independent genes, oestrogen
receptor gene 1 (ESR1) and 2 (ESR2), respectively. E2 is the predominant form of
oestrogen in premenopausal women and is produced primarily by the ovaries in
response to release of luteinising hormone (LH) and follicle-stimulating hormone (FSH)
from the pituitary gland under control of the hypothalamic peptide, gonadotropin-
releasing hormone (GnRH) (Barbieri 2014). E2 production from androgens (e.g.
androstenedione, testosterone) secreted from the ovaries and adrenal glands, is catalysed
by the aromatase enzyme that is encoded by the cytochrome P450 gene, CYP19 (Labrie
et al 2003, Silva et al 2006).
In the classical ER signalling pathway, oestrogens bind to ER, which leads to receptor
dimerisation and nuclear translocation of the dimers. In the nucleus, the ER dimers bind
to DNA sequences based on 13bp oestrogen responsive elements (ERE) that are
generally located in the promoters of target genes, leading to regulation of target gene
expression (Renoir et al 2013). ERα dimers recruit a number of regulatory protein
complexes including the general transcription factor, p300/CREB-binding protein
(p300/CBP), which facilitates chromatin remodelling and exhibits histone
Chapter 1: General Introduction
9
acetyltransferase (HAT) activity that is required for ERα-mediated transcription of
genes (Kim et al 2001). ERα may alternatively activate transcription of genes whose
promoters do not contain a bona fide ERE via interactions with other transcription
factors such as AP1, Sp1, NF-κB, cAMP response element-binding protein (CREB),
p53 and STAT5 which bind to their cognate DNA elements (Thomas and Gustafsson
2011). E2 and ERα effects may also be mediated via non-genomic pathways such as by
ERα interaction with the cytoskeletal protein, p130Cas to activate c-Src and its
downstream pathway, ERK1/2 MAPK. Suppression of p130Cas by siRNA in the breast
cancer cell line, T-47D, abrogates E2-induced increases in c-Src expression and kinase
activity as well as phosphorylated levels of ERK1/2 MAPKs and cyclin D1 expression,
indicating that p130Cas is a critical component in ERα/c-Src non-genomic pathway
(Cabodi et al 2004).
E2-bound ERα and ERβ exhibit opposing effects on the proliferation of breast cancer
cells, with the E2/ERα complex stimulating while E2/ERβ inhibiting breast cancer cell
proliferation (Lindberg et al 2003). As such, the ratio of ERα and ERβ expression is an
important factor in determining the responsiveness of breast cancer cells to oestrogens.
In the ERα-expressing breast cancer cell lines, MCF-7 and T-47D, E2 promotes cell
proliferation but stable transfection of cells to overexpress ERβ results in inhibition of
E2-induced cell proliferation and reduced numbers of colonies in anchorage-
independent growth assays (Omoto et al 2003, Strom et al 2004). ERβ has also been
shown to antagonise E2/ERα-mediated gene transcription. Transfection of an ERβ
expression construct into MCF-7 and T-47D cells and treatment of the cells with E2
downregulated the expression of genes which were initially upregulated in E2-treated
(untransfected) MCF-7 and T-47D cells (Chang et al 2006, Williams et al 2008). These
genes included the cell proliferation-associated gene, c-MYC and the gene encoding
potassium channel subfamily K, member 5 (KCNK5) which regulates ion transport
(Williams et al 2008). As ERα mRNA and protein levels were decreased following
overexpression of ERβ in MCF-7 and T-47D cells, the effects may be mediated by
either or both increased ERβ transcriptional activity and reduced ERα transcriptional
activity due to decreased ERα expression (Chang et al 2006, Williams et al 2008).
Stimulation or inhibition of breast cancer cell proliferation by E2/ERα or E2/ERβ,
respectively, involves modulation of the expression of genes associated with cell
Chapter 1: General Introduction
10
proliferation and apoptosis. In MCF-7 and T-47D cells, E2 treatment rapidly increased
expression of the cell cycle regulators, cyclin D1 and c-MYC within 4-5 hours of
treatment (Prall et al 1998, Wang et al 2011a). Cyclins E and A were also upregulated
in T-47D cells treated with E2, with overexpression of ERβ in the cells abrogating the
increase in cyclin E mRNA levels following E2 treatment (Strom et al 2004). Regulators
of apoptosis are also ER target genes and E2 treatment of MCF-7, T-47D and ZR-75-1
cells decreased apoptosis by inducing expression of the anti-apoptosis factors, BCL2
and BCL-XL (Kandouz et al 1999). While E2 stimulates the growth of ERα+ve breast
cancer cells, in ERα-ve breast cancer cell lines (e.g. MDA-MB-231) transfected with an
ERα expression construct, E2 inhibits proliferation and downregulates expression of
genes which encode cell cycle regulators including cdc2, cyclin B1, cyclin B2 and
cyclin G1 (Moggs et al 2005).
In addition to E2 effects on cell proliferation and survival, the ER pathway has been
implicated in the regulation of angiogenesis, which facilitates tumour growth by
providing a nutrient-rich microenvironment (Elkin et al 2004). In MCF-7 cells, E2
treatment has been shown to increase production of the pro-angiogenic factor, vascular
endothelial growth factor (VEGF) (Applanat et al 2008). Conversely, anti-oestrogens
such as tamoxifen (Section 1.5) decrease E2-induced tumour angiogenesis in mice
transplanted with MCF-7 cells (Lindahl et al 2011).
1.4.2 Progesterone Receptor (PR)
The PR which is expressed in 50-70% of breast tumours is also a member of the nuclear
receptor superfamily (Cui et al 2005). The two most frequently studied PR isoforms in
breast cancer are PRA and PRB, which are commonly co-expressed (Mote et al 2007).
Binding of progesterone to PR leads to the formation of PRA/PRB heterodimers or
PRA/PRA or PRB/PRB homodimers which translocate into the nucleus and bind to
progesterone responsive elements (PRE) to activate transcription of target genes
(Graham and Clarke 2002). A third and shorter PR isoform, PRC has also been
identified which lacks the first zinc finger of the DNA-binding domain but is capable of
stimulating PRA and PRB transcriptional activity (Wei et al 1996, Wei et al 1997).
Expression of PR, an ER target gene, is a marker of good prognosis in ERα-expressing
breast cancers and also predicts responses of these cancers to anti-oestrogens (e.g.
tamoxifen) (Bardou et al 2003, Onitilo et al 2009, Liu et al 2010, Purdie et al 2014).
Chapter 1: General Introduction
11
Progesterone has been shown to induce breast cancer cell proliferation and tumour
growth. Treatment of mouse mammary tumour cell lines with progesterone or the
synthetic progestin, medroxyprogesterone acetate (MPA) increased proliferation, which
was abrogated by the anti-progestin, RU486 (Lamb et al 1999). Consistent with these
studies, the combination of oestrogen and progestin as part of hormone replacement
therapies for postmenopausal women was found to be associated with higher risks of
developing breast cancer compared to that in women who received the placebo or
oestrogen alone (Rossouw et al 2002, Chlebowski et al 2010).
Several recent studies, however, report anti-proliferative effects of progesterone,
especially on E2/ERα-induced proliferation. In human breast tumours propagated as
xenografts in mice, the combination of oestrogens and MPA led to inhibition of tumour
growth (Kabos et al 2012). Similarly, when MCF-7 and T-47D mouse xenografts were
co-treated with oestrogens and progesterone, tumours were smaller than those in mice
treated with oestrogen alone (Mohammed et al 2015). Tamoxifen and progesterone
similarly decreased tumour growth, and the combination of these agents resulted in a
more pronounced inhibition of tumour growth (Mohammed et al 2015). In that study, a
direct interaction between PR and ERα was identified in MCF-7 and T-47D cells, with
activation of PR by progesterone treatment inducing ERα binding predominantly to
PREs instead of EREs. This activated transcription of genes associated with cell death,
apoptosis and differentiation pathways, thereby supporting the anti-proliferative effects
of progesterone/PR (Mohammed et al 2015). Although progesterone and MPA are
reported to both stimulate and repress breast cancer cell proliferation, it is noted that in
studies which show anti-proliferative effects of MPA, high doses of MPA are used and
thus progesterone effects may be dose-dependent (Lamb et al 1999, Kabos et al 2012,
Mohammed et al 2015).
1.4.3 Human Epidermal Growth Factor-Like Receptor 2 (HER2)
Human epidermal growth factor-like receptor 2 (HER2) belongs to a family of four
membrane-bound tyrosine kinase receptors, HER1 or EGFR, HER2, HER3 and HER4
(Iqbal 2014). These receptors contain an extracellular ligand-binding domain, a
hydrophilic transmembrane domain and an intracellular tyrosine kinase domain which is
important for activating downstream signalling pathways. Unlike HER1, HER3 and
HER4, HER2 does not require binding of ligands to the receptor to facilitate
Chapter 1: General Introduction
12
homodimerisation or heterodimerisation with other ligand-activated HER family
members (Dawson et al 2005). Dimerisation of HER2 leads to autophosphorylation of
tyrosine residues in the intracellular domain which triggers activation of pathways that
regulate cell proliferation, survival, angiogenesis and invasion such as the PI3K/AKT,
RAS/MAPK and phospholipase C gamma (PLCγ) pathways (Peles et al 1991, Olayioye
et al 1998). In contrast to HER2 heterodimers, HER2 homodimers are able to regulate
the RAS/MAPK pathway but are not capable of activating PI3K signalling as the
homodimers lack phosphorylated tyrosines in the intracellular domain which facilitate
docking of the receptors to the PI3K pathway adaptor protein, p85 (Soltoff et al 1994,
Muthuswamy et al 1999).
HER2 is overexpressed in 20-25% of breast tumours (Slamon et al 1987, Owens et al
2004). Amplification of the HER2 gene which leads to overexpression of the HER2
protein is associated with a higher histological grade of tumours, with increased risk of
disease recurrence and a poorer prognosis (Press et al 1993, Kim et al 2008). However,
patients with HER2-overexpressing breast cancers benefit from treatment with the anti-
HER monoclonal antibody, trastuzumab (Section 1.5). HER2 is overexpressed in up to
60-70% of ductal carcinoma in situ (DCIS) lesions and HER2 overexpression in pre-
invasive DCIS is proposed to promote progression to invasive breast cancer (Roses et al
2009, Harada et al 2011). This was supported by studies which showed that HER2
expression was associated with more rapid progression of DCIS to invasive ductal
carcinoma (Roses et al 2009, Harada et al 2011).
1.4.4 Androgens and the Androgen Receptor
1.4.4.1 Androgens
Androgens are 19-carbon steroid hormones that regulate male sexual characteristics and
masculinity (Somboonporn and Davis 2004, Shufelt and Braunstein 2008). In women,
androgens are also produced and levels of androgens exceed that of oestrogens, with
dehydroepiandrosterone (DHEA), sulphate-conjugated DHEA (DHEA-S),
androstendione and testosterone produced primarily by the ovaries and adrenal glands
(Burger 2002). Androgens can undergo aromatisation to oestrogens (e.g. E2) in the
presence of aromatase and may be converted to more biologically active androgens (e.g.
5α-dihydrotestosterone (DHT)) by 5α-reductase in peripheral tissues such as the
mammary glands, brain and liver (Labrie et al 2003).
Chapter 1: General Introduction
13
Androgens have anti-proliferative effects on normal breast epithelial cells and the
balance between the levels of androgens and E2 is important during morphogenesis of
the human mammary gland (Rothman et al 2011). During the luteal phase of the
menstrual cycle, the increased E2-to-androgen ratio leads to proliferation of breast
epithelial cells, while in the follicular phase, during which the rate of apoptosis of the
breast epithelium is highest, E2 levels decline and the high E2-to-androgen ratio is
reduced (Rothman et al 2011). Studies in ovariectomised monkeys have indicated that
androgen effects may depend on the presence of oestrogens as treatment of monkeys
with testosterone or E2 alone increased breast epithelial cell proliferation but when both
agents were combined, E2-induced increases in cell proliferation were abrogated (Zhou
et al 2000, Dimitrakakis et al 2003).
1.4.4.2 The Androgen Receptor
The predominant androgen ligands, testosterone and DHT are both capable of binding
to the androgen receptor (AR), however DHT binds with higher affinity (Askew et al
2007). Similar to other steroid hormone receptors, including ERα and ERβ, the AR
belongs to the nuclear receptor superfamily and is comprised of 4 functional domains,
an N-terminal domain (NTD), a DNA-binding domain (DBD), a small hinge region and
a ligand-binding domain (LBD) (Rahman et al 2004, Bennett et al 2010). Androgen
effects in target cells are mediated via activation of AR transcriptional regulation of
gene expression, especially genes that are involved in physiological processes including
cell survival, cell proliferation and cell differentiation. In the absence of ligands, the AR
is held in complexes involving chaperones (e.g. heat shock proteins (HSPs)) and
cytoskeletal proteins (e.g. Filamin A), which direct the AR into a conformation that
facilitates binding of prospective ligands (Cardozo et al 2003, Shatkina et al 2003,
Bennett et al 2010).
In the circulation, testosterone exists either in its free form or is conjugated with
proteins such as albumin or sex steroid hormone-binding globulin (SHBG) (Burger
2002). Upon entering cells, testosterone may be converted into DHT by 5α-reductase.
Testosterone or DHT bind to the AR, resulting in conformational changes which trigger
dissociation of HSPs and cytoplasmic chaperone proteins, and promote recruitment of
co-regulators including ARA70 (Rahman et al 2004). Subsequently, the AR
homodimerises with another ligand-bound AR and translocates into the nucleus where it
Chapter 1: General Introduction
14
binds via its DBD to androgen responsive elements (ARE), which are based on
palindromic sequences separated by 3 nucleotides (5’-AGAACANNNTGTTCT-3’). A
number of regulators are recruited such as histone acetyltransferases (HATs) and co-
regulators of chromatin remodelling, which trigger binding of TATA-binding protein
(TBP), general transcription factors (GTF) and RNA polymerase 2 (RNAPolII) for
initiation of transcription of androgen-responsive genes (Figure 1.4) (Khorasanizadeh
and Rastinejad 2001, Heinlein and Chang 2002, Verrijdt et al 2003).
Figure 1.4: The androgen receptor signalling pathway. In the circulation, testosterone is bound to plasma proteins including sex hormone-binding globulin (SHBG) and upon entering the cell, it may be converted to the non-aromatisable androgen, DHT by 5-reductase. Heat shock proteins (HSPs), which prepare the AR conformation for ligand binding, dissociate from the receptor upon binding of androgen ligands (e.g. DHT). AR dimerises with another ligand-bound AR and the AR dimers translocate into the nucleus where AR binds to androgen responsive elements (ARE) located in the regulatory regions of AR target genes. Co-regulators, the general transcriptional apparatus and RNA polymerase 2 (RNAPolII) are recruited to initiate gene transcription. (Feldman and Feldman 2001).
Following dissociation of androgen ligands from the AR, a nuclear export signal (NES)
located in the LBD facilitates translocation of the receptor into the cytoplasm either for
recycling following ligand binding or for degradation via the proteasome pathway.
Proteasomal degradation is induced by phosphorylation of specific AR residues that
promote ubiquitination of the AR by E3 ubiquitin ligases such as carboxyl-terminus of
Hsc70-interacting protein (CHIP) (He et al 2002, Gaughan et al 2005).
Chapter 1: General Introduction
15
ARE sequences have been identified in a number of target genes that encode regulators
of cell proliferation and survival. For example, functional AREs have been
characterised at -200bp of the cyclin-dependent kinase inhibitor, p21Cip1/Waf1 promoter
(Lu et al 1999), between -570 to -556bp upstream of the transcription start site of the
cyclin D1 gene (Lanzino et al 2010) and between -1320 and -1420bp upstream of the
IGF-1 transcription start site (Wu et al 2007).
1.4.4.3 Androgens and the AR in Breast Cancer
Androgens have been reported to inhibit the growth of breast cancers and these effects
are similar to their roles in normal breast epithelial cells where androgens antagonise
E2/ER-induced increases in cell proliferation (Section 1.4.4.1). Natural (e.g. DHT,
androstenedione) and synthetic (e.g. R1881) androgens inhibit the proliferation of
AR+ve breast cancer cell lines including MCF-7, T-47D and ZR-75-1 (Dauvois et al
1991, Birrell et al 1995, Szelei et al 1997, Ando et al 2002, Ortmann et al 2002, Greeve
et al 2004, Macedo et al 2006). These effects are reversed by co-treatment of the cells
with anti-androgens or AR antagonists such as bicalutamide (casodex) and
hydroxflutamide, indicating that these effects are mediated by the AR (Dauvois et al
1991, Birrell et al 1995, Szelei et al 1997, Ando et al 2002, Macedo et al 2006).
Androgen-mediated inhibition of breast cancer cell proliferation involves
downregulation of expression of cell cycle regulators and upregulation of pro-apoptosis
factors. For example, DHT has been shown to increase the proportion of cells in G1
phase by impeding their progression into S-phase (Greeve et al 2004). This was
associated with decreased expression of cyclin D1 and increased expression of
p21Cip1/Waf1 and p27Kip1 (Greeve et al 2004, Lanzino et al 2010). DHT treatment of ZR-
75-1 cells has also been reported to downregulate the mRNA and protein levels of the
anti-apoptosis factor, BCL2, and to induce apoptosis in MCF-7, T-47D and ZR-75-1
cells (Kandouz et al 1999, Lapointe et al 1999). AR signalling directly induces the
expression of KLLN (killin), a DNA binding protein which increases TP53 and TP73
levels and promotes apoptotic cell death when overexpressed in MCF-7 cells (Wang et
al 2013). Androgen-induced inhibition of breast cancer cell proliferation may also be
mediated via inhibition of E2/ERα-induced cell proliferation and transcriptional activity,
and in MCF-7 and ZR-75-1 cells, DHT inhibited E2-stimulated cell proliferation and
also downregulated E2-induced expression of ERα target genes (Dimitrakakis et al
Chapter 1: General Introduction
16
2003, Need et al 2012). Inhibition of E2 effects and ERα transcriptional activity by
ligand-bound AR requires a functional AR DBD, with this inhibition mediated via
direct interaction between the AR and ERα and AR binding to cellular EREs (Panet-
Raymond et al 2000, Peters et al 2009).
The AR is expressed in 70-90% of breast tumours including ER-ve breast tumours such
as molecular apocrine (ER-ve/HER2+ve/AR+ve) and a proportion of triple-negative
breast cancers (TNBC) (ER-ve/PR-ve/HER2-ve) (Moinfar et al 2003, Safarpour et al
2014). AR expression in breast tumours is more widespread compared to ER (70-80%)
and PR (50-70%) (Kuenen-Boumeester et al 1992) and its expression is associated with
longer relapse-free and overall survival in both ER+ve (Figure 1.5) and ER-ve breast
cancers (Isola 1993, Gonzalez et al 2008, Luo et al 2010, Park et al 2010, He et al 2012,
Kim et al 2015). Molecular clustering of TNBC has identified marked overlapping of
gene signatures between molecular apocrine/TNBC and luminal breast cancers, leading
to the proposal that these cancers may have evolved from luminal subtypes following
loss of ER expression (Farmer et al 2005, Lehmann et al 2011). In support of this
hypothesis, low levels of ER expression were detected in parental cells of the MFM-223
molecular apocrine cancer cell line, which were derived from the pleural effusion of a
breast cancer patient, and following extensive passaging of the cells, ER levels
decreased (Hackenberg et al 1991). Although AR expression in ER-ve breast tumours
has been shown to be associated with longer overall survival of patients (Kim et al
2015), androgens have been proposed to increase the growth of AR+ve/ER-ve breast
cancers, and in cell lines representing molecular apocrine breast cancers (MDA-MB-
453) and TNBC (SUM159PT, BT-549), knockdown of AR reduced cell proliferation,
anchorage-independent growth, cell migration and invasion (Hackenberg et al 1991, Ni
et al 2011, Barton et al 2015).
The mechanisms by which androgens stimulate ER-ve/AR+ve breast cancer cell
proliferation may include activation of ERα-like signalling, WNT and PI3K/AKT
pathways. DNA binding sites for AR in MDA-MB-453 cells overlapped significantly
with those bound by ERα and FOXA1, a transcription factor that is important for ERα
binding to DNA and for ER transcriptional activity (Hurtado et al 2011, Robinson et al
2011). This indicates that AR may have an ERα-like activity in ER-ve breast cancer.
Additionally, DHT has been shown to increase WNT7B mRNA and protein expression
Chapter 1: General Introduction
17
as well as nuclear levels of the β-catenin protein in MDA-MB-453 cells, indicating
activation of WNT signalling (Ni et al 2011). Androgen-induced stimulation of
AR+ve/ER-ve breast cancer cell proliferation may also be mediated by the PI3K/AKT
pathway, with DHT shown to increase phosphorylation of AKT in MDA-MB-453 cells
(Ni et al 2011). While most studies have shown that androgens and the AR stimulate the
growth of AR+ve/ER-ve breast cancer cells, androgens have also been shown to inhibit
MDA-MB-453 cell growth in association with upregulation of PTEN expression,
suggesting that responses of cells to androgens may differ depending on experimental
conditions and potentially due to clonal variation of the cell lines used in the studies
(Wang et al 2011b).
Figure 1.5: Correlation of AR expression in breast tumours and overall survival of patients. AR+ve breast cancers were associated with longer overall survival compared to AR-ve breast cancers (Gonzalez et al 2008).
1.4.4.4 Androgens and AR Modulators as Therapies for Breast Cancer
Androgens such as testosterone propionate, fluoxymesterone and calusterone were
successfully used as breast cancer treatments in the 1970s (Labrie 2006). However, due
to their virilising side effects, liver toxicity that arose in a proportion of patients and the
development of anti-oestrogens, androgen usage in breast cancer management ceased.
More recently, selective androgen receptor modulators (SARM) such as enobosarm
(GTx-024) and GTx-027, have been developed, and these newer generation AR
modulators are associated with greater tissue specificity and may represent a novel
therapeutic strategy for ER+ve breast cancers (Gao and Dalton 2007). A phase 2 clinical
trial is ongoing for enobosarm in patients with metastatic ER+ve breast cancers
(ClinicalTrials.gov Identifier: NCT01616758).
Chapter 1: General Introduction
18
As experimental studies indicate that androgens promote the proliferation of
AR+ve/ER-ve breast cancer cells, clinical trials have also been carried out or are
underway to determine the efficacy of AR antagonists including bicalutamide and
enzalutamide as breast cancer treatments (Gucalp et al 2013, Cochrane et al 2014,
Narayanan et al 2014, Barton et al 2015). A phase 2 clinical trial evaluating
bicalutamide in patients with AR+ve/ER-ve metastatic breast cancers reported that the
drug was well-tolerated, with minor side effects such as fatigue and hot flashes
(ClinicalTrials.gov Identifier: NCT00468715) (Gucalp et al 2013). A proportion of the
patients (~19%) had stable disease for >6 months following treatment with bicalutamide
and the median progression-free survival was 12 weeks, which was similar to trials
evaluating single and combination chemotherapy for triple-negative breast cancers
(O'Shaughnessy et al 2011, Carey et al 2012, Gucalp et al 2013).
1.4.5 The Hedgehog Signalling Pathway
Developmental pathways including the Hedgehog signalling pathway control human
embryonic development and cell/tissue homeostasis by modulating stem cell growth
and differentiation, cell proliferation, survival and migration. However, hyperactivation
of the Hedgehog pathway has been implicated in the development of human cancers
including breast cancer and this frequently involves ligand-dependent induction of the
canonical Hedgehog pathway or constitutive activation or mutation of downstream
Hedgehog signalling intermediates (Cohen 2010).
In the absence of Hedgehog ligands, Sonic Hedgehog (SHH), Indian Hedgehog (IHH)
or Desert Hedgehog (DHH), Patched homologue 1 (PTCH1) receptors inhibit the
activity and translocation to the tip of the primary cilium of a 7-pass transmembrane
protein, Smoothened (SMO). This allows a multiprotein complex consisting of protein
kinase A (PKA), casein kinase 1 (CK1) and glycogen synthase kinase 3β (GSK3β) to
phosphorylate the GLI transcription factors (GLI1, GLI2, GLI3) at the primary cilium,
creating a binding site for the E3 ubiquitin ligase, beta-transducin repeating containing
protein (β-TrCP), which ubiquitinates the GLI transcription factors to induce their
cleavage by the proteasomes. Truncated GLI proteins, which lack C-terminal
transcriptional activation domains, translocate into the nucleus and function as
transcriptional repressors of target genes (Figure 1.6) (Heretsch et al 2010, Wen et al
2010).
Chapter 1: General Introduction
19
Figure 1.6: The Hedgehog signalling pathway. (A) In the absence of Hedgehog ligands, Patched homologue 1 (PTCH1) receptors block the transmembrane protein, Smoothened (SMO) from translocating to the primary cilium. As a result, the Hedgehog effectors, the GLI transcription factors (GLI1, GLI2, GLI3) are phosphorylated by a multiprotein complex comprised of protein kinase A (PKA), casein kinase 1 (CK1) and glycogen synthase kinase 3β (GSK3β) which creates a binding site for the E3 ubiquitin ligase, beta-transducin repeating containing protein (β-TrCP), triggering ubiquitination of the GLI proteins and proteasomal cleavage of GLI. Truncated GLI transcription factors migrate into the nucleus as GLI repressors and downregulate expression of Hedgehog target genes. (B) Binding of Sonic Hedgehog (SHH) to PTCH1 alleviates PTCH inhibition of SMO, thereby allowing SMO to travel to the tip of the primary cilium, where the PKA/CK1/GSK3β containing multiprotein complexes are prevented from phosphorylating GLI transcription factors. Active full-length GLI translocates into the nucleus, where it is able to activate target gene expression (Heretsch et al 2010).
In the presence of Hedgehog ligands (e.g. SHH), binding of SHH to PTCH1 on the
plasma membrane triggers localisation of SMO to the tip of the primary cilium where
SMO binds to the PKA, CK1 and GSK3β containing multiprotein complexes,
preventing phosphorylation of the GLI transcription factors (GLI1, GLI2 and GLI3) and
releasing full-length GLI into the cytoplasm. As such, the GLI transcription factors
retain their transcriptional activation domains and translocate into the nucleus where
they bind to consensus sequences (GACCACCCA) located in gene promoters and
transcriptionally activate the expression of target genes including Hedgehog
intermediates (e.g. PTCH1, GLI1), regulators of cell cycle progression (CCND1,
CCND2) and mediators of epithelial-to-mesenchymal transition (EMT) (e.g. SNAI1,
Chapter 1: General Introduction
20
SNAI2 (SLUG)) (Figure 1.6) (Bonifas et al 2001, Heretsch et al 2010, Winklmayr et al
2010).
1.4.5.1 Hedgehog Signalling in Breast Cancer
A number of in vitro and in vivo studies have provided evidence for the role of aberrant
Hedgehog signalling in the regulation of breast tumorigenesis, breast cancer growth,
cancer stem cell growth, drug resistance and metastasis (Kubo et al 2004, Moraes et al
2007, ten Haaf et al 2009, Cui et al 2010). The Hedgehog signalling intermediates and
Hedgehog target genes, PTCH1, GLI1 and SHH are overexpressed in a proportion of
primary breast cancer specimens with the nuclear localisation of GLI1, which indicates
active Hedgehog signalling, providing evidence for increased activity of the Hedgehog
pathway in tumours compared to adjacent nonmalignant mammary epithelia (Kubo et al
2004). Expression of GLI1, SMO and SHH are also elevated in breast cancer cell lines
such as MCF-7, T-47D, MDA-MB-231 and SKBR3, with inhibition of cell proliferation
observed following treatment with the Hedgehog/SMO inhibitor, cyclopamine (Kubo et
al 2004, Mukherjee et al 2006). In vivo studies have also reported formation of breast
tumours following aberrant activation of the Hedgehog signalling pathway. In female
mice overexpressing Smo in the mammary epithelium, ductal dysplasias with excessive
budding and branching were observed and these phenotypes resembled human breast
hyperplasias (Moraes et al 2007). Similarly, overexpression of Gli1 in the mammary
epithelium of mice led to formation of hyperplastic regions and tumours of ductal,
squamous and solid forms (Fiaschi et al 2009). The Hedgehog signalling pathway also
stimulates breast tumour metastasis. In basal-like breast cancers, paracrine Hedgehog
signalling characterised by high SHH levels in the epithelium and high GLI1 expression
in the stroma was shown to stimulate tumour metastasis, with these effects mediated
principally by activation of Hedgehog signalling in the tumour-associated stroma
(O'Toole et al 2011).
Overexpression of the Hedgehog pathway intermediates, PTCH1 and GLI1, has been
reported in early (e.g. DCIS) and advanced (e.g. invasive ductal carcinoma) breast
tumours, which correlated with younger age at diagnosis (<50 years), poorly
differentiated tumours, lymph node metastasis and poorer overall survival (Moraes et al
2007, O'Toole et al 2011). Recent studies have proposed that Hedgehog signalling
mediates progression of pre-invasive breast lesions such as DCIS to invasive breast
Chapter 1: General Introduction
21
cancers (Souzaki et al 2011). Furthermore, treatment of T-47D cells with recombinant
SHH N-terminal peptide was shown to increase cell invasion, supporting the hypothesis
that the Hedgehog pathway is capable of stimulating the invasiveness of breast cancer
(Souzaki et al 2011).
1.4.5.2 Crosstalk between the Hedgehog Signalling Pathway and Hormone
Receptors
Evidence of cross-talk between the Hedgehog and hormone receptor (e.g. ER, AR)
pathways has been reported. E2 has been shown to increase expression of GLI1 mRNA
in MCF-7 cells, while inhibition of ER signalling by the pure anti-oestrogen, ICI
182,780 was reported to suppress expression of SHH (Koga et al 2008). SHH was also
shown to bind to ERα in co-immunoprecipitation studies but combined targeting of the
ER and Hedgehog pathways with the anti-oestrogen, tamoxifen and Hedgehog
signalling inhibitor, cyclopamine stimulated MCF-7 cell proliferation and migration
(Sabol et al 2014). These findings indicated that combinations of drugs may exhibit
unexpected effects despite the abilities of tamoxifen and cyclopamine to inhibit breast
cancer cell proliferation individually.
Interactions between the AR and Hedgehog pathways have been investigated primarily
in prostate cancer cell lines where androgens stimulate rather than inhibit proliferation
(Shaw et al 2008, Chen et al 2009, Chen et al 2010, Chen et al 2011a). A direct
interaction between the AR and GLI transcription factors, GLI1 and GLI2 has been
reported in the prostate cancer cell line, LNCaP (Chen et al 2010, Chen et al 2011a).
Activation of Hedgehog signalling following androgen ablation therapies was proposed
to sustain the growth of castrate-resistant prostate tumours. In support of this
hypothesis, culture of LNCaP cells in the absence of androgens led to elevation of
PTCH1 and GLI1 levels, indicating activation of Hedgehog pathway transcriptional
activity (Chen et al 2011a). Gene microarray analysis of pathways upregulated in
androgen-independent LNCaP cells which were established by long term culture of
LNCaP cells in androgen-free medium and with the anti-androgen, flutamide, identified
the Hedgehog signalling pathway as a candidate mechanism supporting androgen-
independent prostate tumour growth (Liu et al 2014). Concurrent targeting of the
androgen and Hedgehog signalling pathways may therefore improve the efficacy of
prostate cancer management as evidenced by the synergistic suppression of proliferation
Chapter 1: General Introduction
22
of castrate-resistant prostate cancer cells following treatment with cyclopamine and the
AR antagonist, pyrvinium pamoate (Gowda et al 2013).
1.5 Breast Cancer Treatment
The first-line of therapy for breast tumours is surgery, either mastectomy, a procedure
which removes the entire breast, or breast conserving surgeries such as lumpectomy,
quadrantectomy and segmentectomy, in which the tumour and immediately adjacent
tissues only are removed (Veronesi et al 2002). Following breast conserving surgery or
mastectomy, whole breast irradiation therapy is frequently administered to target
residual tumour cells and this combination has been shown to reduce tumour recurrence
and risk of disease-associated death (Darby et al 2011). Following surgery and radiation
therapy, patients may be treated with adjuvant therapies depending on the classification,
stage and grade of the tumour, and the age and other clinical features of the patient.
Adjuvant chemotherapy is used to treat large tumours (>1cm), node-positive and
metastatic breast cancers. The traditional forms of chemotherapy are the anthracyclines
(cyclophosphamide + methotrexate + 5-fluorouracil (CMF) or doxorubicin +
cyclophosphamide) and taxanes (paclitaxel or docetaxel) (Francis et al 2008). Other
chemotherapeutic agents include capecitabine, gemcitabine, iniparib and platinum-
based compounds such as carboplatin that may be administered as second-line
chemotherapy following disease progression subsequent to anthracycline and taxane
based regimens (Sparano et al 2010, O'Shaughnessy et al 2011).
Hormonal therapies are used to treat ER+ve and/or PR+ve breast tumours and may be
administered as sole agents or in combination with chemotherapy (Wilcken et al 2003,
Puhalla et al 2012). The major classes of hormonal therapies are the selective oestrogen
receptor modulators (SERMs) such as tamoxifen, raloxifene and toremifene, which
interact with the ER and competitively inhibit E2 from binding, and the aromatase
inhibitors, anastrazole, letrozole and exemestane, which block aromatase enzyme
activity and therefore oestrogen production (Demers 1994, Geisler et al 1996, Geisler et
al 1998). Luteinising hormone-releasing hormone (LHRH) agonists, which suppress
ovarian oestrogen production, or oophorectomy may be used in pre-menopausal women
where the ovaries are the main sources of hormones (Goel et al 2009). Tamoxifen has
Chapter 1: General Introduction
23
been used as a first-line adjuvant therapy for ER+ve breast cancers since the 1970s, with
5 years or up to 10 years of continuous tamoxifen treatment recommended following
definitive treatments (e.g. surgery/radiotherapy), a regimen that was found to reduce the
risks of breast cancer recurrence (Davies et al 2013). For node-positive cancers and
tumours larger than 1cm, the combination of tamoxifen and chemotherapy
(cyclophosphamide, doxorubicin, 5-fluorouracil) is frequently used either concurrently
or sequentially (Albain et al 2009, Bedognetti et al 2011).
Aromatase inhibitors are particularly important for the treatment of postmenopausal
women with ER+ve breast cancers as the primary source of oestrogens is peripheral
conversion of androgen precursors to oestrogens via aromatase (Geisler et al 1996,
Geisler et al 1998). In comparison to tamoxifen, treatment with anastrazole has been
associated with increased disease-free survival and reduced rates of distant metastasis or
contralateral breast cancer, with lesser side effects (Howell et al 2005, Mouridsen et al
2009). In recent American Society of Clinical Oncology (ASCO) guidelines, 5 years of
aromatase inhibitor treatment was also recommended for premenopausal women
previously treated with tamoxifen for 5 years (Burstein et al 2014). This has been
supported in clinical trials where letrozole treatment following 5 years of tamoxifen was
shown to increase disease-free survival (Goss et al 2008, Mouridsen et al 2009, Dowsett
et al 2010).
Treatment of HER2-overexpressing breast cancers includes anti-HER2 therapies, most
commonly, trastuzumab (herceptin), an antibody that binds to the juxtamembrane
domain of HER2 (Cho et al 2003). For patients with HER2+ve locally advanced and
metastatic breast tumours, the combination of trastuzumab and chemotherapy such as
docetaxel alone or with vinorelbine or carboplatin have been associated with
improvement in progression-free survival and better overall survival (Andersson et al
2011, Valero et al 2011). For HER2+ve breast tumours which also express ER and PR,
combination treatments, for example, trastuzumab or the EGFR/HER2 tyrosine kinase
inhibitor, lapatinib with anastrazole or letrozole have been associated with longer
progression-free survival compared to aromatase inhibitors alone (Kaufman et al 2009,
Schwartzberg et al 2010). Following progression of tumours treated with first-line anti-
HER2 therapies, regimens including pertuzumab, an alternative anti-HER2 monoclonal
antibody or trastuzumab emtansine (T-DM1), a conjugate of trastuzumab and
Chapter 1: General Introduction
24
maytansinoid, DM1, a microtubule-disrupting agent, have been shown to improve
progression-free survival (Blackwell et al 2012, Swain et al 2013, Krop et al 2014).
Despite advances in the development of targeted agents and combination therapies for
breast cancer, it is not uncommon that treatments fail due to intrinsic or acquired drug
resistance. Cellular processes and mechanisms that have been shown to facilitate drug
resistance include low drug bioavailability due to altered metabolism of therapeutic
drugs, overexpression of the ATP-binding cassette (ABC) drug efflux transporters
which limit intracellular accumulation of drugs (Section 1.6), mutations in drug targets
and activation of secondary growth regulatory pathways to compensate for inhibition of
pathways targeted by therapies (Housman et al 2014).
1.6 The ABC Transporters
Movement of compounds and molecules across the cell membrane is crucial for
homeostasis, the maintenance of a healthy cellular environment. For most membranes,
especially impermeable or lipid membranes, molecules are shuttled in or out of cells or
organelles including the mitochondria, endoplasmic reticulum (ER) and Golgi apparatus
by membrane transporters such as the ABC transporters (Vasiliou et al 2009). The ABC
transporters are ATP-dependent and are expressed in most organisms including
eukaryotes and prokaryotes (Higgins 1992). Depending on the cell type and substrate,
the ABC transporters act as importers and exporters in eukaryotes, whereas in
prokaryotes, ABC transporters mainly import substrates into cells (Vasiliou et al 2009).
A wide variety of molecules are shuttled via these transporters, including ions, sugars,
amino acids as well as therapeutic and chemotherapeutic drugs (Vasiliou et al 2009).
ABC transporter-mediated export of chemotherapeutic agents is a major cause of drug
resistance in cancers, and germline mutations in ABC transporter genes have also been
associated with diseases such as cystic fibrosis and ophthalmic diseases including
Stargardt’s disease and retinitis pigmentosa (Gadsby et al 2006, Vasiliou et al 2009,
Westerfeld 2010).
Chapter 1: General Introduction
25
Figure 1.7: Structural domains of the ABC transporters. (A) ABC transporters are comprised of a cytoplasmic nucleotide-binding domain (NBD) and a membrane-spanning or transmembrane domain (MSD/TMD). (B) Full transporters (ABCB-type) contain 2 NBDs and 2 sets of TMDs that span the lipid bilayer of the plasma membrane. Half-transporters (ABCG-type) consist of only one NBD and one set of TMDs and form homodimers or heterodimers with another half transporter for functional activity (Sarkadi 2006).
The ABC transporters consist of a cytoplasmic nucleotide-binding domain (NDB)
which is made up of highly conserved motifs, the Walker A and B sequences, the H and
Q loops, and a transmembrane or membrane spanning domain (TMD/MSD) (Figure
1.7). Each TMD is encompassed by several hydrophobic α-helices. The NBDs bind
ATP and facilitate its hydrolysis for energy while the TMDs orchestrate movement of
the substrates across the membrane following substrate recognition (Higgins 1992,
Ambudkar et al 2006). Most transporters contain two NBDs and 2 sets of TMDs but a
small subgroup of ABC transporters including ABCG2, which belongs to the G subclass
of the ABC transporter superfamily (ABCG), are synthesised as half-transporters and
require dimerisation or multimerisation with other ABCG2 half-transporters or with
other ABC transporters for efflux activities (Figure 1.7) (Mo and Zhang 2012).
1.6.1 The ABC Transporter Superfamily
In humans, 49 members of the ABC superfamily of transporters have been identified.
These members are classified into 7 subfamilies or subclasses, ABCA, ABCB, ABCC,
ABCD, ABCE, ABCF and ABCG, with mutations in members of each subfamily
associated with various inherited diseases (Table 1.1) (Vasiliou et al 2009).
A B
Chapter 1: General Introduction
26
Table 1.1: The seven subfamilies/subclasses of the ATP-binding cassette (ABC) superfamily (Vasiliou et al 2009).
ABC Transporter Subfamilies
Aliases Number of Genes Number of Pseudogenes
ABCA ABC1 12 5
ABCB MDR 11 4
ABCC MRP 13 2
ABCD ALD 4 4
ABCE OABP 1 2
ABCF GGN20 3 2
ABCG White 5 2
The ABCA or ABC1 subfamily has 12 members which are largely involved in lipid
trafficking (Table 1.1). Eleven members of the ABC transporters belong to the ABCB
subfamily, four of which are full-transporters while the other seven are half-
transporters. The first member of the ABCB subfamily, ABCB1, is the most extensively
studied ABC transporter due to its involvement in the development of multidrug
resistance in multiple types of malignancies (Section 1.6.3.1). The ABCC or MRP
subfamily contains 13 members, several of which are also highly associated with
multidrug resistance, while the ABCD or X-linked adrenoleukodystrophy (ALD)
transporter subfamily includes four half-transporter members which are usually
involved in trafficking of fatty acids. ABCE1 is the only member of the ABCE
subfamily and due to absence of a TMD, it is unlikely that it functions to shuttle
molecules across membranes. Similarly, the three currently known ABCF transporters
also lack TMDs and therefore their role as substrate transporters is also less likely. The
ABCG subfamily of transporters, which consists of at least 5 members is highly
associated with drug transport and multidrug resistance in multiple cancers including
breast cancer (Table 1.1) (Vasiliou et al 2009).
1.6.2 Physiological Roles of the ABC Transporters
ABC transporters are expressed in a wide range of human tissues including the placenta,
lungs, liver, testis and the brain microvasculature where they function as exporters of
mainly hydrophobic substrates including vitamins, sterols and steroid hormones. The
ABC transporters also protect cells and organs by expulsion of metabolites and toxins
Chapter 1: General Introduction
27
that are harmful if allowed to accumulate intracellularly. For example, the liver
expresses ABCB1 and the bile salt pump, ABCB6 and is a major metaboliser of
xenobiotic compounds (Huls et al 2009). Water soluble metabolites are usually excreted
into urine by ABCB1, ABCC2 (MRP2), ABCC4 (MRP4) and ABCG2, all of which are
expressed on the apical surface of proximal tubule cells of the kidney, indicating their
significant role in the excretory system. In liver diseases such as primary biliary
cirrhosis and chronic hepatitis, increased expression of ABCB1 and ABCC3 is
observed, which is thought to represent a physiological response to protect against the
buildup of toxic bile substrates (Ros et al 2003). The ABC transporters also protect the
human foetus from harmful toxins. In the placenta, ABCG2 is expressed at high levels
on the chorionic epithelium of placental villi and is most likely responsible for limiting
exposure of the foetus to harmful toxins or substrates in the maternal circulation
(Maliepaard et al 2001, Ceckova et al 2006). Consistent with this, foetal exposure to
topotecan and dietary toxins was found to be elevated in Abcg2 knockout mice (Abcg2-
/-) (Jonker et al 2000). Further in vivo studies have shown the importance of the ABC
transporters in eliminating toxic metabolites such as porphyrins or degraded chlorophyll
products, as Abcg2-/- mice developed serious phototoxic skin lesions or photoporphyria
when exposed to UV rays following feeding with a chlorophyll-containing alfalfa diet.
This is due to toxic accumulation of pheophorbide A, a type of porphyrin and
breakdown product of chlorophyll (Jonker et al 2002). Plasma levels of the food
carcinogen, 2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP) are also elevated
in Abcg2-/- mice due to decreased intestinal, fecal and hepatobiliary excretion of this
compound which is usually exported by ABCG2 (van Herwaarden et al 2003).
1.6.3 ABC Transporters in Cancer
ABC transporters are major contributors to the development of multidrug resistance
(MDR) in diseases such as cancer. This is primarily attributed to overexpression of
individual ABC transporters in cancer cells and their ability to export a variety of
substrates including therapeutic drugs and chemotherapeutic agents (Kathawala et al
2015). In addition, ABC transporter-mediated drug resistance has been associated with
the cancer stem cell subpopulation of tumour cells, outgrowth of which leads to
treatment failure and cancer relapse (Section 4.1) (Ding et al 2010, Jiang et al 2012,
Zhang et al 2013a). ABCB1, ABCG2, ABCC1 and ABCC10 are the most extensively
studied ABC transporters due to their overexpression in multiple types of cancers. It is
proposed that elucidation of their roles in conferring multidrug resistance in tumours
Chapter 1: General Introduction
28
will facilitate the development of novel therapies to delay or inhibit multidrug resistance
mediated by these transporters.
ABCB1 or P-glycoprotein (P-gp) was the first human ABC transporter identified and
belongs to the first group of the B subfamily (ABCB1) of the ABC transporters. It was
originally isolated in 1986 from a colchicine-resistant keratin-forming tumour cell line
(KB) selected with vinblastine and is encoded by the MDR1 gene (Roninson et al 1986).
In 1992, a second human ABC transporter, multidrug resistance-associated protein 1
(MRP1) or ABCC1 was isolated from the adriamycin-resistant promyelocytic cell line,
HL60/Adr while another member of the MRP family of transporters, MRP7 or ABCC10
was characterised in 2001 (Cole et al 1992, Hopper et al 2001). ABCG2 or breast
cancer resistance protein (BCRP), identified in 1998, belongs to the second group of the
G subfamily of ABC transporter proteins (Doyle et al 1998). ABCG2 was isolated from
a multidrug resistant breast cancer cell line, MCF-7/AdrVp which was selected for
resistance to doxorubicin and verapamil but lacked expression of ABCB1 and ABCC1
(Doyle et al 1998). Simultaneously, two other groups reported isolation of the same
gene but conferred different names to their constructs; mitoxantrone-resistance (MXR)
which was detected in MCF-7 cells and ABCP which was overexpressed in placental
cells (Allikmets et al 1998, Miyake et al 1999).
1.6.3.1 ABCB1 / P-glycoprotein (P-gp)
The ABCB1 or P-glycoprotein (P-gp) gene is located on chromosome 7p21 and contains
28 exons. It encodes a 170 kDa protein comprising of 1280 amino acids and is
expressed predominantly in epithelial cells on apical surfaces of the lower
gastrointestinal tract, proximal tubules of the kidney, liver hepatocytes, the adrenal
glands, placental trophoblasts and capillary endothelial cells of the testes and brain
(Kathawala et al 2015). At these surfaces and typical of the ABC transporters, ABCB1
has a high affinity for binding and export of a diverse array of chemicals and
hydrophobic compounds including chemotherapeutic agents, HIV-protease inhibitors,
antibiotics, anti-depressants and analgesics (Sarkadi 2006). Although a proportion of
these substrates are also transported by other types of ABC transporters, several belong
to drug resistance profiles unique to ABCB1 such as the chemotherapeutic agents,
taxanes (e.g. paclitaxel), colchicine and vinca alkaloids (e.g. vincristine), which are
Chapter 1: General Introduction
29
preferentially effluxed by ABCB1 compared to other transporters (Figure 1.8)
(Kathawala et al 2015).
Figure 1.8: Efflux of chemotherapeutic agents by ABCB1, ABCC1, ABCC10 and ABCG2. ABCB1 and ABCC10 preferentially export taxanes (e.g. paclitaxel) and vinca alkaloids (e.g. vincristine), while ABCC1 mediates export of anthracyclines (e.g. doxorubicin), topotecan and vincristine. ABCB1 has also been shown to export anthracyclines (e.g. doxorubicin, daunorubicin), antibiotics (e.g. actinomycin D) and tyrosine kinase inhibitors (TKIs) (e.g. imatinib, nilotinib). ABCG2 primarily exports anthracyclines (e.g. mitoxantrone, doxorubicin), SN-38, TKIs, methotrexate and flavopiridol (Kathawala et al 2015).
Due to the ability of ABCB1 to efflux a variety of therapeutic agents, cells
overexpressing ABCB1 are often associated with loss of sensitivity to multiple drug
agents. For example, ABCB1 on the luminal surface of microvessel endothelium of the
blood brain barrier (BBB) actively exports chemotherapeutic drugs and as a result, these
drugs are prevented from entering the brain and reaching their target cells or tissues
(e.g. brain cancers such as glioblastomas) (Fellner et al 2002, Hubensack et al 2008).
Therapeutic agents actively exported by ABCB1 include drugs used to treat epilepsy
and antibiotics/antiviral drugs used in the management of infections of the central
nervous system including HIV (Cooray et al 2002, Zhang et al 2003). ABCB1/MDR1
knockout mice (Mrd1a-/-) accumulate higher levels of ABCB1 substrates in the brain,
including the neurotoxic pesticide ivermectin and chemotherapeutic agent, vinblastine,
and the mice are also more sensitive to the effects of these drugs compared to mice
expressing wild-type ABCB1 (Schinkel et al 1997). In addition to drug bioavailability
in the brain, ABCB1 expressed in other areas of the human body limits absorption of
therapeutic drugs such as topotecan. This has been observed following co-
Chapter 1: General Introduction
30
administration of oral topotecan and the P-gp inhibitor, GF120918 to patients who had
solid tumours, where increased oral absorption and bioavailability of topotecan was
induced (Kruijtzer et al 2002). Inhibition of P-gp also decreases the excretion of toxic
metabolites. For example, in the gastrointestinal tract, administration of cyclosporin A,
an immunosuppressive drug which also inhibits P-gp, decreased excretion of irinotecan
hydrochloride (CPT-11) and its metabolite, SN-38 (Arimori et al 2003).
The ABCB1 promoter lacks a TATA box but instead contains an Initiator (Inr) element
essential for transcriptional activation. The proximal promoter region, which spans from
-200bp to +43bp, contains a number of putative Sp1 binding sites as well as binding
sites for transcription factors that potentially regulate ABCB1 transcription (Figure 1.9)
(Scotto 2003, Sarkadi 2006). These include GC-box interacting proteins such as early
growth response protein 1 (EGR1) and Wilms tumour protein (WT1), CAAT-box
interacting proteins, c-Fos, NFκB, and the inverted CCAAT box interacting proteins,
nuclear factor Y (NF-Y) and Y box-binding protein 1 (YB-1) (Figure 1.9) (Sarkadi
2006). The tumour suppressor protein p53 was also found to bind to a head-to-tail (HT)
site in the ABCB1 promoter and when p53 binding to the promoter was disrupted, p53-
induced repression of ABCB1 transcription was lost (Johnson et al 2001b). MDR1
promoter-enhancer factor (MEF1) binds to a region between -118bp and -111bp of the
ABCB1 promoter (Ogretmen and Safa 2000), while heat shock transcription factor 1
(HSF1) binds to elements between -152bp to -178bp of the promoter, often in response
to stress stimuli such as heat shock (Figure 1.9) (Vilaboa et al 2000).
Figure 1.9: Putative binding sites of transcription factors in the ABCB1 promoter. The ABCB1 promoter is TATA-less but contains an Initiator (Inr) element essential for regulation of ABCB1 transcription. Transcription factors whose binding sites have been identified in the ABCB1 promixal promoter region include p53, c-Fos, NFκB, nuclear factor Y (NF-Y), Y box-binding protein 1 (YB-1) and heat shock transcription factor 1 (HSF1) (Scotto 2003).
Chapter 1: General Introduction
31
1.6.3.2 ABCG2 / Breast Cancer Resistance Protein (BCRP)
ABCG2 is located at chromosome 4q22, the gene spans 66kb and consists of 16 exons
and 15 introns. The first exon contains the 5’-untranslated region (5’-UTR) and the
transcription start site is situated in exon 2 (Figure 1.10) (Bailey-Dell et al 2001). The
ABCG2 gene encodes a full-length 72 kDa protein of 655 amino acids (Doyle and Ross
2003). Similar to ABCB1, the ABCG2 gene promoter lacks a TATA box within 100bp
upstream of the transcription start site but contains a CCAAT box in the 5’ region and
several putative Sp1 and transcription factor binding sites (Figure 1.10, 1.11) (Bailey-
Dell et al 2001).
Figure 1.10: The ABCG2/BCRP gene and protein. The ABCG2 gene consists of 16 exons and 15 introns, with the ABCG2 protein translated from exons 2 to 16 (Bailey-Dell et al 2001).
Figure 1.11: Transcriptional regulation of ABCG2. Transcription factors and signalling pathway intermediates such as the Hedeghog pathway effector, GLI1, and TGFβ signalling mediators, SMAD2/3, ER, PR and hypoxia-inducible factor 1 alpha (HIF-1α) regulate ABCG2 transcription via binding to their cognate binding sequences located in the ABCG2 promoter (Natarajan et al 2012).
An ERE and PRE have been identified between -243bp and -115bp of the ABCG2
promoter and ERα has been shown to bind to the ERE located in this region, inducing
ABCG2 mRNA and protein expression in breast cancer cell lines (Figure 1.11; Section
4.1) (Ee et al 2004a, Ee et al 2004b, Yasuda et al 2006). Stress due to hypoxia or low
oxygen conditions has also been shown to stimulate ABCG2 transcription and this
involves direct interaction of hypoxia-inducible factor 1 alpha (HIF-1α) with hypoxia
Chapter 1: General Introduction
32
response elements (HRE) in the ABCG2 promoter (Figure 1.11) (Krishnamurthy et al
2004). Binding sites for signalling pathway intermediates such as the Hedgehog
pathway effector, GLI1 and mediators of the TGFβ pathway, SMAD2 and SMAD3
have similarly been identified in the ABCG2 promoter (Figure 1.11) (Section 4.1)
(Ehata et al 2011, Singh et al 2011).
ABCG2 is widely expressed, for example, in the apical membrane of placental
syncytiotrophoblasts, liver hepatocytes, intestinal mucosal cells, endothelial cells of the
blood brain barrier (BBB), the ovaries, prostate cells and the proximal tubules of the
kidney (Sarkadi 2006). Similar to other members of the ABC transporter superfamily,
ABCG2 primarily exports hydrophobic and amphiphilic compounds. In addition to
these endogenous compounds, ABCG2 is also an active exporter of a variety of drugs
and its elevated expression is associated with the development of multidrug resistance
in cancer (Nakanishi 2012, Kathawala et al 2015). ABCG2 substrates include
chemotherapeutic agents such as mitoxantrone, camptothecins and their analogues,
flavopiridol, topoisomerase 1 inhibitors (e.g. topotecan), irinotecan and its metabolite,
SN-38, and the antifolate agent, methotrexate (Figure 1.8) (Maliepaard et al 2001,
Kathawala et al 2015). Fluorescent compounds or dyes such as Rhodamine 123,
BODIPY-prazosin, Hoechst 33342 and pheophorbide A are also actively exported by
ABCG2 and due to their fluorescence, are useful as probes for examining ABCG2
efflux activities (Mao and Unadkat 2015).
Consistent with their abilities to export multiple chemotherapeutic drugs, the ABC
transporters including ABCG2 are overexpressed in multiple types of cancers, for
example, haematological and lymphoid malignancies including acute myeloid
leukaemia as well as solid tumours including breast, lung, colon, and gastric carcinomas
(Natarajan et al 2012). In acute lymphoblastic leukaemia (ALL), elevated ABCG2
mRNA expression has been associated with shorter survival (Suvannasankha et al
2004). Similarly, in solid tumours, overexpression of ABCG2 has been correlated with
lower response rates to chemotherapy, and lower progression-free and overall survival
(Diestra et al 2002, Yoh et al 2004, Lee et al 2012).
Chapter 1: General Introduction
33
1.6.3.2.1 ABCG2 in Breast Cancer
Although ABCG2 was first isolated in a breast cancer cell line, ABCG2 does not appear
to be highly expressed in human breast tumours and is not extensively characterised.
Using immunohistochemistry and semi-quantitative RT-PCR, low to undetectable
ABCG2 levels were detected in breast tumours and these were not correlated with
clinical features of the tumours, treatment responses or disease prognosis (Kanzaki et al
2001, Faneyte et al 2002). In a later study, ABCG2 expression in primary breast tumour
samples detected using RT-PCR was shown to be associated with lower response rates
to anthracycline-based chemotherapy consisting of 5-fluoroacil, adriamycin/epirubicin
and cyclophosphamide, although results did not reach statistical significance (Burger et
al 2003). Similarly, in a cohort of Chinese breast cancer patients, ~50% of the patient
specimens were shown to express ABCG2 and this was also correlated with resistance
to 5-fluorouracil (5-FU) (Yuan et al 2008). More recently, ABCG2 expression in the
small population of breast cancer stem cells has been described and may represent the
major function of ABCG2 in breast tumours (Section 4.1).
1.6.3.2.2 ABCG2 Protein Structure and Synthesis
Unlike ABCB1, ABCG2 is a half-transporter and is composed of a NBD and a set of
TMDs which consists of six α-helices (TM1-TM6) (Figure 1.12) (Nakanishi 2012).
Homo- or heterodimerisation of two half-transporters is crucial for functional activation
of ABCG2 as a plasma membrane transporter. Fluorescence resonance energy transfer
(FRET) and crystallography studies have shown that ABCG2 assembles into
homodimers or homooligomers and a functional tetrameric complex of four ABCG2
homodimers has also been demonstrated (McDevitt et al 2006, Ni et al 2010).
Activation of ABCG2 as a full transporter at the plasma membrane involves several
post-translational regulatory events (summarised in Figure 1.13) (Natarajan et al 2012).
Homodimerisation of ABCG2 is initially believed to involve disulphide bond linkages
at cysteine 603, although others have reported intact and functional ABCG2 despite loss
of this cysteine residue (Ni et al 2010, Haider et al 2011). Following synthesis, ABCG2
also undergoes N-linked glycosylation at asparagine 596, which is located in the
extracellular loop between helices TM5 and TM6 of the ABCG2 transmembrane
domain. In addition, formation of intramolecular disulphide bonds between cysteine 592
and 608 is required to maintain protein stability (Figure 1.13) (Diop and Hrycyna 2005,
Chapter 1: General Introduction
34
Henriksen et al 2005). Mature oligomeric and fully glycosylated ABCG2 transporters
are usually degraded via the lysosomal degradation pathway, whereas hypoglycosylated
and mis-folded ABCG2 are preferentially targeted for proteasomal degradation (Figure
1.13) (Wakabayashi et al 2007).
Figure 1.12: Structural domains of the ABCG2 half-transporter. Half-transporters such as ABCG2 are comprised of a NBD and a set of TMDs which consists of 6 α-helices (TM1-TM6). In the extracellular loop 3 (ECL3) region between TM5 and TM6 are cysteine residues at positions 592, 603 and 608, which have been shown to regulate formation of disulphide bonds between ABCG2 dimers, and asparagine at position 596 which is required for N-linked glycosylation of ABCG2 (Nakanishi 2012).
Substrate specificity of ABCG2 is regulated by the identity of amino acid 482 of the
ABCG2 protein, and wild-type ABCG2 primarily exports mitoxantrone but is a weak
exporter of Rhodamine 123 (Honjo et al 2001, Robey et al 2003). A single nucleotide
change at position 482 from an arginine in wild-type ABCG2 (e.g. in the MCF-7 breast
cancer cell line) to either a glycine (R482G) or threonine (R482T), which was identified
in cells selected for resistance to chemotherapy (e.g. MCF-/AdVp3000), increases the
ability of ABCG2 to transport substrates other than mitoxantrone, including Rhodamine
123, doxorubicin and anthracyclines (Honjo et al 2001, Robey et al 2003). Additional
structural studies have determined that the COOH terminus of the ABCG2
transmembrane domain, which functions as an interface for drug-transporter
interactions, is positioned in close proximity to amino acid 482 in the mature protein
and is capable of altering interactions of substrates with the transporters (Ejendal et al
2006).
Chapter 1: General Introduction
35
Figure 1.13: Post-translational modification and plasma membrane trafficking of ABCG2. ABCG2 is N-glycosylated and undergoes homodimerisation via formation of intramolecular disulphide bonds to form mature ABCG2 that functions as a substrate exporter at the plasma membrane. Mature ABCG2 is usually degraded by the lysosomes but mis-folded and/or hypoglycosylated ABCG2 may be targeted for degradation by the proteasomal pathway (Natarajan et al 2012).
1.6.3.3 ABCC / Multidrug Resistance Protein (MRP)
The ABCC or MRP members of the ABC superfamily of transporters, ABCC1 (MRP1)
and ABCC10 (MRP7) are most extensively studied for their roles in multidrug
resistance. ABCC1 encodes a 190 kDa transporter protein which when overexpressed in
cancer cells leads to resistance to a diverse array of chemotherapeutic agents that are
also able to be effluxed by other ABC transporters including ABCB1 and ABCG2
(Krishnamachary and Center 1993). These agents include anthracyclines (e.g.
doxorubicin), topotecan, vinca alkaloids (e.g. vincristine), methothrexate, and
mitoxantrone, although taxanes (e.g. paclitaxel, docetaxel), which are known ABCB1
substrates, are not exported by ABCC1 (Figure 1.8) (Kathawala et al 2015). Confirming
the importance of ABCC1, embryonic fibroblasts from ABCC1 (MRP1) knockout mice
(Mrp1-/-) exhibited greater sensitivity to vincristine compared to fibroblasts isolated
from wild-type mice (Johnson et al 2001a).
Chapter 1: General Introduction
36
The ABCC10 gene is located at chromosome 6p21.1 and encodes a 171 kDa transporter
protein which consists of three TMDs and two NBDs. ABCC10 is ubiquitously
expressed in the human body including the gastrointestinal tract, kidney, colon, heart,
brain and pancreas (Hopper et al 2001, Kathawala et al 2015). Unlike ABCC1,
ABCC10 is an active exporter of taxanes as well as vincristine and gemcitabine, and
mouse embryo fibroblasts isolated from ABCC10 knockout mice (Abcc10-/-)
accumulated higher levels of the chemotherapeutic drugs, docetaxel and paclitaxel
(Hopper-Borge et al 2011). Consistent with these findings, increased lethality of
Abcc10(-/-) mice was observed following treatment with paclitaxel (Hopper-Borge et al
2011).
1.6.4 Modulators of the ABC Transporters
Due to the significant contribution of the ABC transporters to the development of
multidrug resistance in cancers, up to 3 generations of modulators or inhibitors of ABC
transporter expression and/or function have been developed and tested in pre-clinical
and clinical studies. The first generation of ABC transporter inhibitors included
verapamil, cyclosporine A (CSA) and quinine, however these agents were unsuitable for
clinical use primarily due to high toxicity and low efficacy in patients. A phase III
randomised study in 1995 showed that a combination of verapamil and the
chemotherapeutic agents, vincristine, doxorubicin or dexamethasone did not exhibit
beneficial effects but was associated with cardiotoxicity (Dalton et al 1995). Second
generation ABC transporter modulators such as valspodar and biricodar were
subsequently developed and also tested in clinical trials. Although these agents showed
higher efficacy than the first generation of modulators, they were associated with
development of side effects in patients including ataxia and dizziness (Friedenberg et al
2006). A number of third generation ABC transporter modulators (e.g. zosuquidar
(LY335979) and tariquidar (XR9576)) have also been developed. In clinical trials for
metastatic and locally recurrent breast cancer, non-Hodgkin’s lymphoma and acute
myeloid leukaemia, co-administration of zosuquidar and chemotherapy was safe but did
not improve progression-free and overall survival (Fracasso et al 2004, Morschhauser et
al 2007, Ruff et al 2009, Cripe et al 2010). Tariquidar in combination with docetaxel
has been evalueted in lung and ovarian cancer patients and similarly, results were not
sufficiently pronounced to warrant continuation of the trial (Kelly et al 2011). Specific
inhibitors of ABCG2 including the micotoxin, fumitremorgin C (FTC), and its more
potent and less toxic analogue, KO143, which impedes ABCG2 function and ATPase
Chapter 1: General Introduction
37
activity by binding with higher affinity to ABCG2 in a competitive manner, have been
used extensively in pre-clinical studies. (Allen et al 2002). FTC and KO143 have not
been evaluated in clinical trials likely due to toxicity associated with these compounds,
especially FTC, which induces tremors, convulsions and toxicity to the central nervous
system of animals (Nishiyama and Kuga 1989, Nishiyama and Kuga 1990).
A number of tyrosine kinase inhibitors including the BCR-ABL (breakpoint cluster
region-Abelson tyrosine kinase) inhibitors, imatinib and nilotinib, and the EGFR
inhibitors, lapatinib, erlotinib and gefitinib, inhibit ABC transporter function by
blocking ATP binding and availability (Dai et al 2008, Shen et al 2009). Several of
these agents are also substrates of the ABC transporters and may induce competitive
inhibition of ABC transporter function for other substrates (Burger et al 2004, Shen et
al 2009). For example, lapatinib was reported to impede ABCB1 and ABCG2 efflux
activities in vitro, resulting in intracellular accumulation of the ABC substrates,
doxorubicin or mitoxantrone in ABCB1 and ABCG2 overexpressing MCF-7 cells,
although ABCB1 and ABCG2 mRNA and protein levels were unchanged (Dai et al
2008). Consistent with these results, lapatinib also enhanced the inhibitory effects of
paclitaxel on the growth of ABCB1-overexpressing KBv200 cell xenografts in nude
mice (Dai et al 2008). Although pharmacological targeting of ABC transporters is a
logical treatment strategy for cancer, in particular to prevent or overcome drug
resistance, the important functions of ABC transporters at the blood brain barrier and
their pivotal physiological roles in the kidney and liver have limited their clinical use.
1.7 Epithelial-to-Mesenchymal Transition (EMT)
Epithelial-to-mesenchymal transition (EMT) is a reversible physiological process
involving separation of epithelial cells that are usually interconnected in organised
structures by cell-to-cell and cell-to-extracellular matrix (ECM) bonds and
transformation of these cells to irregular-shaped mesenchymal-like cells which are more
motile and invasive (Yilmaz and Christofori 2009). Physiologically, EMT is crucial in
embryonic development, for example, during gastrulation, which leads to development
of the mesoderm and endoderm, and for neural crest formation, during which
mesenchymal cells migrate to various sites of the body to develop into more specialised
tissue-specific cells such as glial and neuronal cells of the central nervous system,
Chapter 1: General Introduction
38
adrenal glandular cells and melanocytes (Nistico et al 2012). In adults, EMT contributes
to wound healing and remodelling of tissues such as the mammary gland, in which
lobular and ductal cells undergo specialised differentiation and proliferation at the onset
of puberty (Silberstein 2001, Nistico et al 2012). However, when the EMT programme
is perturbed or hyperactivated, it can result in a number of pathological conditions
including inflammation, fibrosis and cancer progression (Nistico et al 2012).
1.7.1 Physiological Processes Mediating EMT
The initiation and progression of EMT involves a sequence of events that is associated
with reduced expression and function of epithelial-specific and cell-to-cell adhesion
molecules (e.g. E-cadherin, claudins, occludin and cytokeratin) and increased
expression of mesenchymal markers (e.g. N-cadherin, vimentin, fibronectin), core EMT
transcription factors (e.g. SNAI1, SLUG, ZEB1, ZEB2) and basic helix-loop-helix
proteins (e.g. TWIST1, TWIST2) (Figure 1.14) (Huber et al 2005, Tsai and Yang
2013). The EMT transcription factors including SNAI1 and SLUG are capable of
repressing expression of the epithelial marker, E-cadherin by binding to E-box
sequences located in the promoter of the E-cadherin gene, CDH1 (Figure 1.14) (Batlle
et al 2000, Hajra et al 2002).
In response to pro-EMT signals including activation of the transforming growth factor β
(TGFβ), WNT and NOTCH pathways (Section 1.7.2.1, 1.7.2.2, 1.7.2.3), cell-to-cell
adhesion complexes (Section 1.7.1.1) which normally form strong bonds between
neighbouring cells are dissociated. Subsequently, cell surface receptors bind to ECM
components, resulting in the formation of focal adhesion complexes (Section 1.7.1.2)
that re-organise the structure of the intracellular actin cytoskeleton, which is connected
to the cell-to-cell adhesion complexes in epithelial cells. This leads to changes in cell
morphology and formation of protrusions (e.g. invadopodia, lamellipodia) at cell edges
to facilitate cell migration. In order for cells to invade into the surrounding ECM and
stroma, the ECM is degraded by serine proteases such as matrix metalloproteinases
(MMPs) (Section 1.7.1.3) and epithelial cells transdifferentiate into mesenchymal-like
cells which adhere poorly to other cells and are more motile (Figure 1.14) (Lamouille et
al 2014).
Chapter 1: General Introduction
39
Figure 1.14: Epithelial-to-mesenchymal transition (EMT). Following activation of the EMT programme, a series of physiological events including tight junction dissociation, loss of apical-basal polarity, cytoskeletal re-organisation, cell migration and degradation of the basement membrane facilitate transformation of organised structures of epithelial cells into motile and fibroblast-like mesenchymal cells. The hallmarks of EMT include downregulated expression of epithelial markers (E-cadherin, claudins, occludins, zona occludens 1 (ZO-1), desmoplakin, cytokeratins) and upregulation of mesenchymal marker expression (N-cadherin, fibronectin, vimentin) (Aroeira et al 2007).
1.7.1.1 Cell-to-Cell Adhesion Complexes
Re-organisation of cell-to-cell adhesion complexes is a crucial step during EMT that
results in dissociation of the strong bonds which normally exist between neighbouring
epithelial cells and fibroblasts. Examples of these complexes include the adherens
junctions (zonula adherens), desmosomes (macula adherens) and tight junctions (zonula
occludens) (Figure 1.15) (Kawauchi 2012).
The two different forms of adherens junctions are the cadherins such as E-cadherin and
N-cadherin, and the nectins and nectin-like proteins (Kawauchi 2012). Nectins are
immunoglobulin-like molecules which are connected to the actin cytoskeleton through
afadin, an actin-binding protein. In contrast, the intracellular domains of cadherins
interact with β-catenin and p120-catenin, with β-catenin recruiting α-catenin to mediate
connection of the catenin/cadherin complex to the intracellular actin cytoskeleton via
actin binding proteins such as vinculin and EPLIN (Figure 1.15) (Abe and Takeichi
2008, Kawauchi 2012).
Similar to the adherens junctions, desmosomes and tight junctions also enforce cell
adhesion and are connected to the actin cytoskeleton. Desmosomal components, which
Chapter 1: General Introduction
40
are abundant in the skin and myocardium are composed of non-classical cadherins such
as desmogleins and desmocolins which bind to intracellular plakoglobin, plakophilin
and desmoplakin to connect the cell adhesion proteins to actin microfilaments (Figure
1.15). Plakoglobin, plakophilin 2 (PKP2) and desmogleins have also been reported to
strengthen cadherin and desmosome based cell adhesion via a different mechanism
involving the E-cadherin/β-catenin complexes (Lewis et al 1997). Tight junctions are
characteristically located at the apical section of the lateral membrane of epithelial and
endothelial cells and examples of molecules comprising this family of junction proteins
include zona occludens 1 and 2 (e.g. ZO-1, ZO-2), members of the claudin family (e.g.
claudin-1, claudin-7), occludin and junction adhesion molecule (JAM) (Figure 1.15)
(Kawauchi 2012). In addition to their role in controlling the integrity of cell-to-cell
adhesion, tight junctions also regulate cellular absorption of essential ions such as
sodium (Na+), chloride (Cl-), calcium (Ca2+), and magnesium (Mg2+) to maintain
electrolyte balance via transport of these ions through small intercellular spaces at tight
junctions between epithelial cells (paracellular diffusion) (Tang and Goodenough 2003).
Figure 1.15: Adhesion complexes between adjacent cells and the ECM. Cells are interconnected by (A) tight junctions (TJ), adherens junctions (AJ), gap junctions and desmosomes which are often disrupted during EMT. (B) Nectins and cadherins are adherens junction proteins whereas (C) desmocollin and desmoglein are desmosomal proteins and (D) claudins, junctional adhesion molecule (JAM) and occludins are tight junction proteins. (E) During EMT, cell surface proteins such as the integrins bind to components of the ECM to stimulate cell invasion. Activated integrins bind to downstream proteins such as talin, focal adhesion kinase (FAK) and vinculin which are linked to filamentous actin (F-actin). As the cell adhesion proteins are linked to the intracellular actin cytoskeleton or F-actin and intermediate filaments, disruption of cell-to-cell adhesion leads to reassembly of the actin cytoskeleton and changes in cell morphology (Kawauchi 2012).
Chapter 1: General Introduction
41
1.7.1.2 Integrin-Mediated Focal Adhesions
Formation of focal adhesions involving the integrins serves two purposes: to act as a
bridge between the ECM and intracellular actin cytoskeleton and for signal transduction
to regulate cell proliferation, survival and motility. In humans, the integrin family of
transmembrane proteins contains 18 α-chains and 8 β-chains which form at least 24
combinations of α-β heterodimers (Kawauchi 2012). Components of the ECM such as
fibrillar collagens (collagens I-III, V, XI), proteoglycans (e.g. aggrecan, versican,
decorin) and glycoproteins (e.g. laminins, elastin, fibronectin) bind to cell surface
receptors including the integrins and increase formation of focal adhesions at
filamentous actin (F-actin)-based adhesion sites or hemidesmosomes which are
intermediate filament-based (Figure 1.15). Overproduction and deposition of collagen
and crosslinking of collagen by lysyl oxidase (LOX) and LOX-like (LOXL) enzymes,
which leads to stiffening of the ECM, also stimulates formation of focal adhesions and
consequently increases activation of intracellular signalling pathways (Xiao and Ge
2012).
Focal adhesion complexes are composed of intracellular molecules such as talin,
vinculin, zyxin, SRC, focal adhesion kinase (FAK), paxilin and p130Cas. The
connection between focal adhesions and the intracellular actin cytoskeleton is mediated
via talin which binds to the cell surface β1 integrins as well as vinculin, an adaptor
protein that interacts with α-actinin, paxilin, vinexin and vasodilator-stimulated
phosphoprotein (VASP) once its conformation is switched to an active open structure.
α-Actinin and vinculin, in turn, bind to F-actin (Figure 1.15) (Kawauchi 2012).
Additionally, integrins regulate cell proliferation, survival and migration via activation
of other intracellular pathways/intermediates such as the focal adhesion kinases (FAKs),
the SRC family of kinases, MAPK, NFκB and WNT/β-catenin pathways (Kuwada and
Li 2000, Mitra et al 2005, Chung et al 2009, Groulx et al 2014). For example,
interaction of paxilin with FAK leads to formation of complexes consisting of FAK, a
SRC kinase and Grb2, which activates the downstream growth regulatory RAS/MAPK
pathway. Alternatively, vinexin may bind to an activator of Ras, Sos, to activate the c-
Jun N-terminal kinase/stress-activated kinase (JNK/SAPK) pathway (Figure 1.15)
(Akamatsu et al 1999).
Chapter 1: General Introduction
42
In order for cells to undergo spreading and migration, formation of focal adhesions
anchors cells to the ECM and provides the forces crucial for pushing the cells forward
in the direction of migration. Subsequently, turnover of the focal adhesions is required
for cells to become motile and migrate from their stationary positions (Webb et al
2002). Overexpression of the actin-binding protein, vinculin, but not other molecules,
has been reported to inhibit cell migration by inducing the maturation and stabilisation
of focal adhesions (Rodriguez Fernandez et al 1992, Saunders et al 2006).
1.7.1.3 Matrix Metalloproteinases (MMPs)
Invasion of cells into the extracellular spaces or stroma requires ECM component-
degrading enzymes such as the matrix metalloproteinases (MMPs) to detach cell-to-cell
and cell-to-ECM adhesions as well as to create a track or pathway in the ECM for cells
to migrate. The 23 human MMPs are divided into collagen-cleaving MMPs or
collagenases (MMP1, MMP8, MMP13), gelatin (denatured collagen)-cleaving MMPs
or gelatinases (MMP2, MMP9) and MMPs that degrade a variety of ECM components,
the stromelysins (MMP3, MMP10, MMP11) and matrilysins (MMP7) (Radisky and
Radisky 2010). These proteolytic enzymes cleave their substrates via direct binding to
specific domains of the target molecules. For example, type 1 collagens bind to the N-
terminal domain of gelatinases whereas stromelysins and collagenases interact with
collagens at the C-terminal domains of the enzymes (Allan et al 1991, Murphy et al
1992, Allan et al 1995).
1.7.2 Regulation of EMT by Signalling Pathways
EMT is regulated by a number of pathways that are also associated with cell and tissue
development and cancer. The major pro-EMT pathways include the TGFβ, WNT and
NOTCH signalling pathways, activation of which modulates the expression of the EMT
markers, vimentin and fibronectin, the core EMT transcription factors, SNAI1, SLUG
and TWIST1, as well as the cell-to-ECM components, integrins and collagens.
1.7.2.1 TGFβ Pathway
The TGFβ signalling pathway is an important regulator of cellular processes including
cell proliferation, cell differentiation, apoptosis, migration and invasion (Talbot et al
2012). In the canonical TGFβ pathway, the cytokine TGF-β, which is secreted as a
precursor molecule (latent TGF-β) in large latency complexes (LLCs), binds to the cell
Chapter 1: General Introduction
43
surface receptor, TGF-β receptor 2 (TGFβ-RII) following its release from the LLCs
(Figure 1.16). Along with TGF-β receptor 3 (TGFβ-RIII), ligand-bound TGF-β
receptors form heterotrimeric complexes with and transphosphorylate TGF-β receptor 1
(TGFβ-RI), which in turn phosphorylate the downstream ligand-specific receptor-
activated SMADs (R-SMADs), SMAD2 and SMAD3. R-SMADs then form
heteromeric complexes with SMAD4, a co-SMAD molecule, and translocate into the
nucleus where they function as transcription factors (Figure 1.16) (Talbot et al 2012).
As SMAD proteins bind with low affinity to DNA, transcription factors and co-
regulators such as p300/CBP, forkhead activin signal transducer-1 (FOXH1), E26
transformation-specific 1 (ETS1), AP-1 and AP-2 bind to SMAD to regulate
transcription of genes (Chen et al 1997, Janknecht et al 1998, Zhang et al 1998,
Koinuma et al 2009). Examples of TGFβ pathway-regulated target genes include those
associated with EMT (e.g. vimentin, SNAI1, SLUG), the human plasminogen activator
inhibitor-type 1 gene (PAI-1 or SERPINE1), collagens (e.g. COL1A2), and integrins
(e.g. ITGA5) (Chen et al 1998, Dennler et al 1998, Lai et al 2000, Romano and Runyan
2000, Peinado et al 2003, Yoshida et al 2013).
In addition to their regulation by the SMAD-dependent TGFβ pathway, signalling by
TGFβ also regulates apoptosis, cell migration, invasion and EMT via other pathways
that are independent of SMAD. These include activation of the Rho family of GTPases
(e.g. RhoA/Rock1), and MAP kinases such as ERK1/2, c-JUN N-terminal kinase (JNK)
and p38 kinases (Engel et al 1999, Yue and Mulder 2000, Yu et al 2002, Ozdamar et al
2005). For example, TGFβ-induced alteration of cell-to-cell adhesion during EMT can
be mediated via interaction of TGFβ-RI with Par6, a regulator of epithelial cell polarity
and tight junction assembly. This results in phosphorylation of Par6 which triggers
interaction of Par6 with an E3 ubiquitin ligase, SMAD ubiquitylation regulatory factor 1
(SMURF1), to target the regulator of actin cytoskeleton, RhoA, for degradation, leading
to dissociation of tight junctions (Ozdamar et al 2005). The TGFβ pathway is also
capable of activating the p38 MAPK pathway, independent of SMAD, to mediate a
TGFβ-induced EMT-like programme. In mouse mammary epithelial cells (NMuMG),
TGF-β1 treatment led to formation of spindle-shaped cells and downregulation of E-
cadherin expression in cell junctions, and these phenotypes were inhibited when cells
were co-treated with the p38 kinase inhibitor, SB203580 (Yu et al 2002).
Chapter 1: General Introduction
44
Figure 1.16: TGFβ signalling. TGF-β released from large latency complexes (LLCs) binds to TGF-β receptor 2 (TGFβ-RII) which, in association with TGF-β receptor 3 (TGFβ-RIII), forms heterotrimeric complexes with and transphosphorylates TGF-β receptor 1 (TGFβ-RI). SMAD2/3 proteins are phosphorylated by these complexes and conjugate with SMAD4 to initiate their nuclear translocation and transcriptional regulation of genes. SMAD-independent pathways regulated by TGFβ include the Traf6-TAK1-p38/JNK, RhoA-Rock1 and Par6 pathways, all of which may regulate cell proliferation, migration and invasion (Talbot et al 2012).
1.7.2.2 The WNT Signalling Pathway
Both canonical and non-canonical WNT signalling pathways play crucial roles in the
regulation of cell survival, proliferation, migration and invasion. In the canonical WNT
pathway, binding of canonical WNT ligands (e.g. WNT2, WNT2B, WNT8B, WNT3A,
WNT6, WNT9A, WNT10B) to their receptor complexes composed of a 7-
transmembrane domain receptor, Frizzled (Fz) (e.g. FZD1, FZD7) and lipoprotein
receptor-related protein 5/6 (LRP5/6) promotes plasma membrane localisation of a
cytosolic protein complex containing Axin, a negative regulator of WNT signalling.
Chapter 1: General Introduction
45
This allows binding of Axin to a conserved sequence in the cytoplasmic tail of LRP5/6
which leads to activation and membrane localisation of a phosphoprotein, Dishevelled
(DSH) (Mao et al 2001, Zeng et al 2008). DSH inhibits the activity of the enzyme
GSK3β, thereby preventing phosphorylation and degradation of β-catenin, which is
normally mediated by a destruction complex that contains Axin, adenomatous polyposis
coli (APC), GSK3β and casein kinase 1 (CK1) (Figure 1.17). As a result, β-catenin is
able to translocate into the nucleus where it binds to and functions as a co-activator of
T-cell factor/lymphoid enhancer factor (TCF/LEF) complexes to increase expression of
WNT target genes, for example, cyclin D and c-MYC (He et al 1998, Shtutman et al
1999, Komiya and Habas 2008). In the absence of WNT signalling, the destruction
complexes remain in the cytosol where CK1 and GSK3β phosphorylate β-catenin,
promoting its targeting by the E3 ubiquitin ligase, β-TrCP and proteasomal-mediated
degradation (Figure 1.17) (Komiya and Habas 2008).
Figure 1.17: The canonical WNT signalling pathway. In the absence of WNT signalling, the destruction complex consisting of Axin, adenomatous polyposis coli (APC), GSK3β and casein kinase 1 (CK1) phosphorylates β-catenin in the cytoplasm and induces binding of E3 ubiquitin ligases that promote proteasomal-mediated degradation of β-catenin. Binding of WNT ligands to Fz receptors releases β-catenin from the destruction complexes, resulting in accumulation of β-catenin in the cytoplasm and subsequently its nuclear translocation. In the nucleus, β-catenin acts as a co-activator of T-cell factor/lymphoid enhancer factor (TCF/LEF)-mediated WNT target gene expression (Komiya and Habas 2008).
Chapter 1: General Introduction
46
Non-canonical WNT signalling, which is independent of β-catenin-mediated
transcriptional regulation of genes, includes the planar cell polarity (PCP) (Figure 1.18)
and WNT/Ca2+ (Figure 1.19) pathways. In the PCP pathway, binding of non-canonical
WNT ligands (e.g. WNT5A, WNT5B, WNT11) or WNT4 and WNT7B, which are able
to regulate both canonical and non-canonical WNT signalling, to Fz receptors (e.g.
FZD3, FZD4, FZD6) activates downstream pathways, involving the small GTPases,
Rho and Rac (Figure 1.18) (Benhaj et al 2006, Komiya and Habas 2008). In WNT/Rho
signalling, DSH forms complexes with and activates Dishevelled associated activator of
morphogenesis 1 (Daam1) which then activates Rho-associated kinases (ROCK) and
myosin to modulate the structure of the actin cytoskeleton (Figure 1.18) (Komiya and
Habas 2008). In contrast, activation of Rac is Daam1-independent and results in the
regulation of JNK signalling to modulate actin polymerisation and gastrulation (Figure
1.18) (Komiya and Habas 2008).
Figure 1.18: The non-canonical WNT/planar cell polarity (PCP) pathway. Signals from WNT binding to Fz receptors induce formation of Dishevelled (Dsh) and Dishevelled associated activator of morphogenesis 1 (Daam1) complexes which activate either the actin-binding protein, profilin or the small GTPases Rho and Rac to modulate the actin cytoskeleton and induce cytoskeletal re-arrangement (Komiya and Habas 2008).
The WNT/Ca2+ pathway is important in embryogenesis, for example, where it functions
as a critical regulator of cellular processes including EMT and cell migration in the
formation of the dorsal axis, cardiogenesis and gastrulation. In this pathway, signals
from WNT and Fz stimulate release of Ca2+ from the endoplasmic reticulum (ER) that
activate Ca2+-sensitive proteins including protein kinase C (PKC) and
Chapter 1: General Introduction
47
calcium/calmodulin-dependent kinase 2 (CAMK2) (Kuhl et al 2000, Sheldahl et al
2003). PKC has a role in the control of cell-sorting behaviour in the mesoderm during
gastrulation via activation of the small GTPase CDC42, while CAMK2 is able to
activate the TGFβ-activated kinase (TAK1) which stimulates Nemo-like kinase (NLK)
activity and downregulates β-catenin/TCF transcriptional activity via direct binding to
the TCF4 transcription factor (Figure 1.19) (Ishitani et al 1999, Winklbauer et al 2001).
Figure 1.19: The non-canonical WNT/Ca2+ pathway. Binding of WNT ligands to Fz receptors induces activation of Dishevelled (Dsh) which stimulates the release of Ca2+ from the endoplasmic reticulum (ER). WNT signalling regulates a number of developmental process via multiple pathways that are mediated by activation of calcineurin, protein kinase C (PKC) and calcium/calmodulin-dependent kinase 2 (CAMK2). Calcineurin stimulates the activity of the transcription factor, nuclear factor of activated T cells (NFAT), PKC activates the small GTPase CDC42 while CAMK2 antagonises the transcriptional activation of β-catenin/TCF via activation of TGFβ-activated kinase (TAK1) and Nemo-like kinase (NLK), which directly inhibits TCF4 (Komiya and Habas 2008).
1.7.2.3 The Notch Signalling Pathway
NOTCH signalling is another developmental pathway shown to regulate cell
proliferation, differentiation, apoptosis and EMT. The NOTCH pathway is activated
Chapter 1: General Introduction
48
following interactions of canonical ligands, Delta or Serrate/Jagged (Jagged1 and
Jagged2) with NOTCH receptors (NOTCH 1-4) in adjacent cells. This promotes
cleavage of the receptors by γ-secretase to release the NOTCH intracellular domain
(NICD) which translocates into the nucleus where it binds to the transcriptional
repressor, CBF-1, Suppressor of Hairless and Lag-2 (CSL) to de-repress and co-activate
the transcription of NOTCH target genes such as the Hairy enhancer of split (Hes)
family members (Figure 1.20) (Wang and Zhou 2013).
Figure 1.20: The Notch signalling pathway. At junctions between adjacent cells, binding of Notch ligands (Delta/Jagged) to their receptors induces ubiquitination of the intracellular domain of Notch receptors and their cleavage by metalloproteases and gamma-secretase. This leads to the release of Notch intracellular domains (NICDs) into the cytoplasm and their translocation into the nucleus where they bind to CSL transcription factors. In the presence of transcriptional coactivators, expression of Notch target genes (e.g. helix-loop-helix transcription factors, HRT/Herp transcription factors, p21, NRARP, deltex-1) is increased (Talbot et al 2012).
SLUG is an example of a NOTCH target gene, and in the nonmalignant breast epithelial
cell line, MCF10A, SLUG expression is upregulated following constitutive activation of
NOTCH (Leong et al 2007). SLUG downregulates E-cadherin mRNA and protein
expression and induces an EMT-like programme involving dissociation of cell–cell
adhesions and formation of cells with a spindle-shaped morphology (Leong et al 2007).
NOTCH effects on EMT may also be mediated via activation of the TGFβ and NFκB
signalling pathways (Zavadil et al 2004, Wang et al 2006), with downregulation of
NOTCH1 by siRNA reversing NOTCH1-induced increases in pancreatic cancer cell
Chapter 1: General Introduction
49
invasion in association with decreased binding of NFκB to DNA and reduced
expression of MMP9 (Wang et al 2006).
1.7.3 EMT in Breast Cancer
The process of tumour metastasis involves a series of events, a proportion of which may
be regulated by induction of an EMT process. Cancer-associated EMT facilitates
migration and invasion of tumour cells which, after entry into the blood or lymphatic
circulation (intravasation), may be transported to a secondary site. Following
extravasation, where the tumour cells invade through the vessel wall into the underlying
tissue, EMT signals are lost and reversal of EMT or mesenchymal-to-epithelial
transition (MET) is instigated, permitting formation of micrometastases. MET is
essential for cancer cell dissemination and proliferation at a new site as EMT regulators
(e.g. SNAI1) inhibit cell division by reducing the expression of the cell cycle regulator,
cyclin D (Vega et al 2004).
Loss of E-cadherin expression is one of the hallmarks of EMT (Section 1.7.1).
Decreased expression of E-cadherin is correlated with cancer aggressiveness and
metastasis, with lower levels of E-cadherin expressed in advanced stage tumours (e.g.
lymph node-positive breast cancer) (Younis et al 2007). Formation of β-catenin/E-
cadherin complexes at cell-to-cell junctions is important for maintaining epithelial
integrity, and increased nuclear β-catenin in breast tumours, which indicates activation
of β-catenin/WNT signalling, is associated with poorer treatment outcomes and worse
disease prognosis (Yoshida et al 2001). An EMT signature is characteristic of the more
aggressive basal-like breast cancers, and includes elevated expression of both
mesenchymal markers (vimentin, smooth muscle actin, N-cadherin, cadherin 11) and
molecules which stimulate ECM remodeling and invasion (SPARC, laminin, fascin),
but reduced levels of epithelial markers (E-cadherin, cytokeratins) (Sarrio et al 2008).
Altered cell-to-cell adhesion structures regulate EMT progression and in cancers
including breast tumours, lower expression of tight junction proteins has been
demonstrated in metastatic tumours, with poorly differentiated and higher grade breast
tumours shown to express lower levels of ZO-1 (Martin et al 2004, Martin et al 2010).
The EMT core transcription factor, SNAI1 has also been reported to downregulate
occludin mRNA levels, while claudin-1 expression was suppressed only at the protein
Chapter 1: General Introduction
50
level, indicating regulation by post-translational modification (Ohkubo and Ozawa
2004).
In order to stimulate cell migration and invasion, a number of regulators of cell-to-ECM
and matrix metalloproteinases are also altered in tumours. The integrins have different
roles in breast tumour migration and invasion depending on their heterodimerisation
partners. Expression of the α6β4 integrins has been associated with larger and higher
grade tumours and αvβ3 integrins were found to induce bone metastasis of breast
tumours (Diaz et al 2005, Takayama et al 2005). In an in vivo mouse model of HER2-
overexpressing breast cancer, knockdown of β4 integrin by expression of a dominant
negative mutant of this integrin subunit was associated with inhibition of tumorigenesis
and metastasis (Guo et al 2006). High mRNA and protein expression of the β6 integrin
subunit in breast tumours is also associated with poor survival of patients and distant
metastases (Moore et al 2014). In contrast, in the poorly differentiated Mm5MT cell
line, a mouse mammary tumour virus (MMTV)-induced tumorigenic breast cancer cell
line, exogenous expression of α2β1 integrins transitioned the spindle-shaped and motile
cells into cells with more epithelial-like and less invasive phenotypes, indicating that
α2β1 integrins have an inhibitory effect on EMT and metastasis (Zutter et al 1995).
Similarly, low expression of α5β1 integrin has been associated with poor differentiation
of breast adenocarcinomas (Zutter et al 1990), although contrasting studies have also
reported pro-invasive effects of α5β1 integrins that are implicated in EMT in mammary
epithelial cells (Maschler et al 2005). For example, knockdown of steroid receptor
coactivator-1 (SRC-1) in mouse mammary tumour cell lines reduced cell migration
which was associated with downregulation of the expression of ITGA5, a gene encoding
the α5 integrin, and decreased ability of cells to assemble focal adhesion complexes for
cell migration. (Qin et al 2011). Elevated expression of α5β1 integrins has also been
shown to increase breast cancer cell invasion via modulation of MMP-1 and MMP-2
collagenase activity (Jia et al 2004, Morozevich et al 2009).
Due to the ability of MMPs to induce cell invasion into the surrounding stroma and
ECM, MMPs have been hypothesised to play important roles in the progression of
DCIS to invasive cancers. In support of this hypothesis, expression of MMP9, MMP26
and tissue inhibitor of metalloproteinases, TIMP-2 and TIMP-4 were higher in DCIS
compared to adjacent nonmalignant breast epithelium and invasive ductal carcinomas
Chapter 1: General Introduction
51
(Zhao et al 2004). In invasive breast tumours, MMPs were shown to be expressed at
high levels in intratumoral stromal fibroblasts and fibroblasts at the invasive front of
breast tumours (Del Casar et al 2009). In breast cancer cell lines, MMP2, MMP9 and
MMP14 were found to be expressed at higher levels in more invasive (MDA-MB-231
and Hs578T) compared to less invasive (MCF-7, ZR-75-1) cell lines, while MMP1 and
MMP7 were overexpressed only in the more invasive MDA-MB-231 cell line
(Kousidou et al 2004, Figueira et al 2009).
Abnormal activation of pro-EMT signalling pathways is implicated in breast cancer cell
migration, invasion and tumour metastasis. Expression of TGF-β1 has been reported in
human mammary carcinomas with the levels shown to be higher at the leading edges of
the tumours and in lymph node metastases (Dalal et al 1993). In vitro, TGF-β1
treatment of MCF-7 cells was shown to induce a fibroblast-like phenotype, reduce cell-
to-cell interactions and promote cell migration and invasion, while transplantation into
rats of 13762NF mammary adenocarcinoma clone MTLN3 cells that had been pre-
treated with TGF-β1 increased formation of lung metastases (Welch et al 1990, Zhang
et al 2013b).
Similarly, both WNT/β-catenin and non-canonical WNT signalling pathways stimulate
breast tumour metastasis often in association with overexpression of WNT signalling
intermediates (e.g. WNT ligands, Fz receptors) (Wu et al 2012, MacMillan et al 2014).
Knockdown of WNT3A in herceptin-resistant SKBR3 and BT-474 breast cancer cell
lines, in which WNT signalling is hyperactivated, led to inhibition of cell invasion,
decreased nuclear localisation of β-catenin and reversal of EMT, with N-cadherin
expression downregulated and E-cadherin upregulated (Wu et al 2012). WNT5A, a
ligand of the non-canonical WNT signalling pathways also stimulates breast cancer
metastasis. This is supported by in vitro studies using cell lines derived from patients
with invasive mammary carcinomas where transfection of the cells with a WNT5A
expression construct stimulated cell migration and invasion, which were associated with
upregulation of MMP3 (MacMillan et al 2014). The NOTCH signalling pathway
increases expression of EMT transcription factors (e.g. SLUG), and in the breast cancer
cell lines, MCF-7 and MDA-MB-231, ectopic expression of the NOTCH intracellular
domain (NICD) resulted in increased cell invasion, while knockdown of NOTCH1
Chapter 1: General Introduction
52
reversed EMT and cell invasion in vitro and in vivo in mice injected with NOTCH1
shRNA-transfected MDA-MD-231 cells (Bolos et al 2013, Shao et al 2015).
1.8 Statement of Aims
The androgen receptor (AR) and Hedgehog signalling pathways alter the expression of
genes that encode positive and negative regulators of breast cancer cell proliferation,
differentiation, survival and motility. A direct interaction between the AR and the
Hedgehog signalling effectors, the GLI transcription factors has been reported,
suggesting potential cross-talk between the pathways (Chen et al 2010, Chen et al
2011a). Androgens including DHT inhibit the proliferation of AR+ve/ER+ve/PR+ve
breast cancer cells and inhibition of the Hedgehog signalling pathway with the SMO
inhibitor, cyclopamine, has similarly been shown to decrease breast cancer cell
proliferation. (Greeve et al 2004, Macedo et al 2006, Mukherjee et al 2006, Zhang et al
2009). Expression of breast cancer-associated genes following DHT and/or cyclopamine
treatment of the MCF-7 and T-47D breast cancer cell lines, which was investigated
using RT2 Profiler Human Breast Cancer PCR Arrays, identified marked
downregulation of transcripts encoding the ABC drug efflux transporter, ABCG2,
overexpression of which is associated with drug resistance and is a hallmark of breast
cancer stem cells (Kim et al 2002, Engelmann et al 2008). Expression of EMT
regulators was also decreased in DHT and cyclopamine treated cells, indicating that
EMT-associated processes including migration and invasion are also inhibited (Yilmaz
and Christofori 2009, Lamouille et al 2014). Based on these preliminary findings, the
aims of this thesis were:-
1. To investigate DHT and cyclopamine effects on the expression and function of
ABCG2 in MCF-7 and T-47D cells
2. To evaluate DHT and cyclopamine-induced regulation of EMT in MCF-7 and T-
47D cells
Chapter 2
Materials
Chapter 2: Materials
53
2.1 Reagents
2.1.1 Cell Culture
CellTiter 96® AQueous One Solution cell proliferation assay
Promega, USA
Charcoal-treated foetal calf serum (CSS) Serana Australia, Australia
Foetal calf serum (FCS) Serana Australia, Australia
MCF-7 breast cancer cell line American Type Culture Collection, USA
Penicillin (10,000 U/mL)/streptomycin (10,000 μg/mL)
Life Technologies, USA
RPMI 1640 medium (with L-glutamine) ICN Biochemicals Inc, USA
T-47D breast cancer cell line American Type Culture Collection, USA
Trypsin-EDTA Life Technologies, USA
2.1.2 Immunofluorescence Microscopy
Bovine serum albumin Sigma, USA
Chlorobutanol BDH Biochemicals, UK
Hoechst 33258 Sigma, USA
Horse serum Life Technologies, USA
Formaldehyde BDH Biochemicals, UK
Immersion oil Nikon, Japan
Lysotracker Red Life Technologies, USA
Nail polish (clear) Manicare, Australia
Phalloidin tetramethylrhodamine B isothiocyanate (Phalloidin red)
Sigma, USA
Polyvinyl alcohol BDH Biochemicals, UK
Sodium azide Aldrich Chemical Company, USA
Sodium dihydrogen orthophosphate dihydrate BDH Biochemicals, UK
Chapter 2: Materials
54
Triton-X 100 Sigma, USA
2.1.3 Flow Cytometry and Cell Sorting
7-Aminoactinomycin D A.G. Scientific, USA
Hoechst 33342 (bisBenzimide H 33342 trihydrochloride)
Sigma, USA
Mitoxantrone Pfizer, Australia
Rhodamine 123 Sigma, USA
2.1.4 Western Blotting
Acrylamide (37.5:1), 40% (w/v) Amresco, USA
Colour Plus® pre-stained protein marker New England Biolabs, UK
Developer solution A& B Agfa, Belgium
ECL reagent GE Healthcare, USA
Glycine Amresco, USA
2-Mercaptoethanol (2-ME) BDH Biochemicals, UK
NP40 (Igepal) Sigma, USA
Phenylmethylsulphonyl fluoride (PMSF) Roche, Australia
Protease inhibitor cocktail tablets A.G. Scientific, USA
Skim milk powder Bonlac Foods Ltd, Australia
Sodium dodecyl sulphate (SDS) BioRad, USA
Sucrose BDH Biochemicals, UK
Tween-20 Sigma, USA
2.1.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing
1kb Plus DNA ladder™ Life Technologies, USA
Agarose Amresco, USA
Big Dye® Terminator v3.1 cycle sequencing kit Applied Biosystems, USA
Chapter 2: Materials
55
dNTP set (dATP, dTTP, dCTP, dGTP) Promega, USA
Ethidium bromide ICN Biochemicals Inc, USA
GoTaq® qPCR master mix Promega, USA
Magnesium chloride Life Technologies, USA
Oligo(dT) Promega, USA
Platinum® Taq DNA polymerase Life Technologies, USA
Primers: ABCG2 Sense: 5’-GTT TCA GCC GTG GAA CTC TTT G-3’ Anti-sense: 5’-GCA TCT GCC TTT GGC TTC AAT-3’
Geneworks, Australia
Primers: AR Sense: 5’-CCT GGC TTC CGC AAC TTA CAC-3’ Anti-sense: 5’-GGA CTT GTG CAT GCG GTA CTC A-3’
Geneworks, Australia
Primers: β-actin Sense: 5’-GCT GAT CCA CAT CTG CTG GAA-3’ Anti-sense: 5’-ATT GCC GAC AGG ATG CAG AA-3’
Geneworks, Australia
Primers: GAPDH Sense: 5’-TGA GGT CAA TGA AGG GGT C-3’ Anti-sense: 5’-GTG AAG GTC GGA GTC AAC G-3’
Geneworks, Australia
RNasin® ribonuclease inhibitor Promega, USA
RT2 SYBR green qPCR master mix Qiagen, Australia
Sodium acetate BDH Biochemicals, UK
2.1.6 General
Baxter water Baxter, Australia
Boric acid, sodium decahydrate (borax) Amresco, USA
Bromophenol blue BDH Biochemicals, UK
Chloroquine Sigma, USA
Chapter 2: Materials
56
Cyclopamine LC Laboratories, USA
5α-Dihydrotestosterone (DHT) Sigma, USA
Disodium hydrogen orthophosphate BDH Biochemicals, UK
Dimethyl sulfoxide (DMSO) Braun Medical, USA
EDTA BDH Biochemicals, UK
Ethanol Rowe Scientific, Australia
Glacial acetic acid Sigma, USA
Glycerol Sigma, USA
Hydrochloric acid BDH Biochemicals, UK
Isopropanol Merck, Australia
KO143 hydrate Sigma, USA
Matrigel™ (growth factor reduced) BD Biosciences, USA
Methanol Labserv, Australia
MG132 A.G. Scientific, USA
Potassium chloride BDH Biochemicals, UK
Potassium dihydrogen orthophosphate BDH Biochemicals, UK
Sodium chloride Sigma, USA
Sodium hydroxide BDH Biochemicals, UK
Sodium hydroxide pellets Sigma, USA
Toluidine blue O Amresco, USA
Tris Amresco, USA
2.2 Laboratory Equipment
2.2.1 Cell Culture
Acrocap™ filter unit (with 0.2 μm Supor® membrane)
Pall Corporation, Mexico
Acrodisc™ syringe filter (with 0.2 μm Supor® Pall Corporation, Mexico
Chapter 2: Materials
57
membrane)
CellStar® culture flask (25 cm2) Greiner Bio-One, Germany
CellStar® culture flask (75 cm2) Greiner Bio-One, Germany
CellStar® culture plate (6-well) Greiner Bio-One, Germany
CellStar® culture plate (12-well) Greiner Bio-One, Germany
CellStar® culture plate (24-well) Greiner Bio-One, Germany
CellStar® culture plate (96-well) Greiner Bio-One, Germany
CellStar® petri dish (100×20 mm) Greiner Bio-One, Germany
CO2 humidified incubator Sanyo, Japan
Nikon Eclipse TS1000 phase contrast microscope
Nikon, Japan
5 mL Sterile tubes Sarstedt, Australia
10 mL Sterile tubes Sarstedt, Australia
15 mL Sterile tubes Sarstedt, Australia
50 mL Sterile tubes Sarstedt, Australia
Powerpette® turbo pipette controller Jencons, UK
Tucsen® IS500 camera Xintu Photonics, China
2.2.2 Immunofluorescence Microscopy
Lean-lite lightbox Lean Pty Ltd, Australia
Microscope cover glass (22×22 mm) Menzel-Glaser, Germany
Microscope slide (26×76 mm) Knittel Glass, Germany
Nikon A1 confocal laser microscope Nikon, Japan
Nikon Eclipse Ti-E microscope Nikon, Japan
2.2.3 Flow Cytometry and Cell Sorting
BD FACSCanto™ II BD Biosciences, USA
BD Influx™ Cell Sorter BD Biosciences, USA
Chapter 2: Materials
58
Canto tube TechnoPlas, Australia
Falcon™ tube with cell strainer cap (35 µm nylon mesh)
Falcon, USA
2.2.4 Western Blotting
Agfa CP1000 developer Agfa, Belgium
CL-Xposure™ clear blue X-ray film Thermo Fisher Scientific, USA
Mini Protean® Tetra Cell BioRad, USA
Nitrocellulose membrane Amersham Biosciences, UK Whatman International, USA
Ortho regular CURIX screens (autoradiography cassette)
Agfa, Belgium
PTC-100™ programmable thermal controller MJ Research Inc, USA
Sonicator Branson, USA
Whatman® 3MM filter paper Whatman International, USA
2.2.5 Agarose Gel Electrophoresis, PCR, RT-qPCR, Sanger Sequencing
384-well PCR microtitre plate Axygen Inc, USA
Agarose gel electrophoresis gel tank Fisher Biotec, Australia
C1000™ Thermal cycler BioRad, USA
Corbett liquid handling robot Corbett Life Science, Australia
3730 DNA Analyser Thermo Fisher Scientific, USA
Gel Doc 2000 EQ BioRad, USA
Light Cycler® 480 Roche, Australia
Nanodrop® ND-1000 spectrophotometer Thermo Fisher Scientific, USA
Qik Spin microcentrifuge United Biosciences, Australia
Qubit® fluorometer Life Technologies, USA
Rotorgene-6000 Corbett Life Science, Australia
RT2 Profiler Human Breast Cancer PCR Array Qiagen, Australia
Chapter 2: Materials
59
(PAHS-131Z)
RT2 Profiler Human EMT PCR Array (PAHS-090Z)
Qiagen, Australia
2.2.6 General
384-well Labofuge T centrifuge Heraeus Sepatech, USA
Aluminium foil KaterMaster, Australia
Autoclave steriliser AMSCO, USA
BioCoat™ Matrigel™ invasion chambers Corning, USA
Centrifuge (5415C, 5415R, 5810R) Eppendorf, Australia
Cling wrap KaterMaster, Australia
Conductive tips (1000 µL) Tecan, USA
Document scanner (HP2500 Precision) Hewlett Packard Pty Ltd, Australia
-20ºC Freezer Westinghouse, USA
-80ºC Freezer Forma Scientific, USA
Latex examination gloves Ansell, Australia
Magnetic stirrer Industrial Equipment and Control Pty Ltd, Australia
Microcentrifuge tube (0.2 mL) Eppendorf, Australia
Microcentrifuge tube (0.5 mL) Eppendorf, Australia
Microcentrifuge tube (1.5 mL) Eppendorf, Australia
Milipore masterflex pump Cole-Parmer, USA
Multi-channel pipette (20-200 μL) Axygen Inc, USA
Needle (23G) Terumo, Japan
Olympus BX43 microscope Olympus, USA
Parafilm Pechiney, USA
pH Cube pH-mV-temperature meter TPS, Australia
Pipette tips (0.1-10 μL) Axygen Inc, USA
Pipette tips (0.1-200 μL) Sarstedt, Australia
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60
Pipette tips (200-1000 μL) Quality Scientific Plastics, USA
Power Pac 300 electrophoresis power supply BioRad, USA
Shaker Hoefer Scientific, USA
120 mL Specimen container Thermo Fisher Scientific, Australia
Surgical blade Swann-Morton, England
Syringe (1 mL) Becton, Dickinson and Company, Belgium
Syringe (50 mL) Terumo, Japan
Transfer pipette Samco Scientific, USA
UVM 340 Microplate reader Asys, UK
Vortex Select BioProducts, USA
Waterbath Thermoline Scientific, Australia
2.3 Antibodies
Alexafluor® 488 goat anti-mouse IgG Life Technologies, USA
Alexafluor® 546 goat anti-mouse IgG Life Technologies, USA
Anti-ABCG2 (BXP-21), produced in mouse Abcam, USA
Anti-AR, produced in mouse (Clone: AR441) Dako, Australia
Anti-α-tubulin, produced in mouse (Clone: DM1A)
Sigma, USA
Anti-β-actin, goat polyclonal IgG (Clone: I-19) Santa Cruz Biotech Inc, USA
Anti-goat IgG-HRP, produced in donkey Santa Cruz Biotech Inc, USA
Anti-histone H3, produced in mouse Cell Signalling, USA
Anti-mouse IgG-HRP GE Healthcare, USA
Allophycocyanin (APC) anti-human CD44 (Clone: C26), produced in mouse
BD Biosciences, USA
Brilliant Violet™ 421 (BV421) anti-human CD24 (Clone: ML5), produced in mouse
BD Biosciences, USA
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61
Phycoerythrin (PE) anti-human CD24 (Clone: ML5), produced in mouse
BD Biosciences, USA
2.4 Commercial Kits
QIAquick® PCR purification kit 2 mL collection tubes QIAquick® spin columns Buffer PB Buffer PE Buffer EB
Qiagen, Australia
RNase-free DNase set DNase1 (lyophilised) (1500 kunitz units) Buffer RDD
RNase-free water
Qiagen, Australia
RNeasy® mini kit
2 mL collection tubes 1.5 mL microcentrifuge tubes RNeasy® mini spin columns Buffer RLT Buffer RW1 Buffer RPE (concentrate) RNase-free water
Qiagen, Australia
RT2 First strand cDNA kit GE (5× gDNA elimination buffer) RNase-free water BC3 (5× RT buffer 3) P2 (Primer and external control mix) RE3 (RT enzyme mix 3)
Qiagen, Australia
Superscript™ III first strand synthesis
Superscript™ III 0.1 M DTT 5× First strand buffer
Life Technologies, USA
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62
2.5 Computer Programmes
Adobe® Photoshop CS Adobe, USA
AutoQuant X3 Media Cybernetics, USA
BD FACSDiva 6.0 BD Biosciences, USA
cellSens™ software Olympus, USA
Chromas Lite 2.1.1 Technelysium, Australia
EndNote™ X5 Thomson Reuters, USA
FlowJo FlowJo, USA
Image J National Institute of Health (NIH)
ISCapture software Xintu Photonics, China
KIM software Asys, UK
Light Cycler® 480 software 1.5 Roche, Australia
Microsoft Office™ (Excel, Powerpoint, Word) Microsoft, USA
NIS-Elements™ Nikon, Japan
Prism® 5.0 GraphPad, USA
Quantity One® BioRad, USA
Rotorgene-6000 software 1.8 Corbett Life Science, Australia
RT2 Profiler PCR array data analysis version 3.4 Qiagen, Australia
TScratch 1.0 The MathWorks, Inc., USA
Chapter 3
Methods
Chapter 3: Methods
1, 2, 3 etc reference to Appendix 1 (Buffers and Solutions)
3.1 Cell Culture
The human breast adenocarcinoma cell lines, MCF-7 and T-47D, used in this thesis
were obtained from the American Type Culture Collection. MCF-7 cells were originally
isolated in 1973 from the pleural effusion of a breast cancer in a 69 year old Caucasian
female (Soule et al 1973). T-47D cells were cultured from the pleural effusion of a
breast cancer in a 54 year old woman in 1979 (Keydar et al 1979).
3.1.1 Maintenance of Breast Cancer Cell Lines
MCF-7 and T-47D cells were routinely cultured in 75 cm2 cell culture flasks in RPMI
1640 medium supplemented with 10% foetal calf serum (FCS), 10,000 U/mL penicillin
and 10,000 μg/mL streptomycin (PS) (RPMI/10%FCS/PS)41 at 37ºC and 5% CO2 in
humidified incubators. Culture medium was replaced every 2-3 days and cells were
passaged at 80-90% confluency every 5-8 days. To passage cells, medium was
aspirated, cells were rinsed with 2-3 mL PBS32 then incubated with 1-2 mL trypsin-
EDTA at 37ºC for 2-3 min to dislodge cells. Trypsinisation was inhibited by the
addition of 3-5 mL RPMI/10%FCS/PS41 and the cell suspension was aliquotted into
new culture flasks or plates as required. MCF-7 and T-47D cells were passaged
routinely at dilutions of 1:5 and 1:6, respectively.
3.1.2 Cryopreservation of Cell Lines
To cryopreserve MCF-7 and T-47D cells, RPMI/10%FCS/PS41 medium supplemented
with 10% DMSO was prepared and stored at 4ºC, MCF-7 and T-47D cells were
trypsinised (Section 3.1.1) and the cell suspensions centrifuged at 260 g for 5 minutes at
room temperature. Supernatants were aspirated, the cell pellets were resuspended on ice
in RPMI/10%FCS/PS41 containing 10% DMSO at 3 mL per 75 cm2 flask and 1 mL
aliquots of the cell suspensions were added to cryovials. Cryovials were placed in
insulated containers overnight at -80ºC, then transferred to liquid nitrogen.
3.1.3 Thawing of Cell Lines
To thaw cells, cryovials were placed in a 37ºC waterbath until cell suspensions were
just thawed, then the cell suspensions were immediately added dropwise into a 75 cm2
culture flask containing 10 mL pre-warmed RPMI/10%FCS/PS41. Flasks were
Chapter 3: Methods
64
incubated overnight at 37ºC, 5% CO2 to allow the cells to adhere prior to replacement of
the culture medium.
3.1.4 Isolation of Breast Cancer Stem-Like Cells
Breast cancer stem-like cells were isolated from the MCF-7 cell line using fluorescence-
activated cell sorting (FACS) (Section 3.5) (Kim et al 2002, Engelmann et al 2008). To
prepare cultures, MCF-7 cells grown in 75 cm2 culture flasks were incubated at 37ºC
and 5% CO2 in 10 mL RPMI/10%FCS/PS41 containing 5 µg/mL Hoechst 3334223 for 60
minutes, the cells were trypsinised and the trypsin inactivated by addition of
RPMI/10%FCS/PS41 (Section 3.1.1). Cell suspensions containing 60×106 cells were
centrifuged at 260 g for 5 minutes at room temperature, supernatants were aspirated and
1 mL RPMI 1640 medium containing 2% FCS, 10,000 U/mL penicillin and 10,000
μg/mL streptomycin (RPMI/2%FCS/PS)41 was added to the cell pellets. Cells were
incubated with 1:5 (v/v) allophycocyanin (APC)-conjugated anti-CD44 (CD44-APC)
and 1:5 (v/v) phycoerythrin (PE)-conjugated anti-CD24 (CD24-PE) or 1:50 (v/v)
Brilliant Violet™ 421 (BV421) anti-CD24 (CD24-BV421) antibodies for 30 minutes on
ice, then 5 mL RPMI/2%FCS/PS41 was added to the cell suspensions, which were
centrifuged at 260 g for 5 minutes at 4ºC. Supernatants were removed, cell pellets were
re-suspended in 6 mL RPMI/2%FCS/PS41 and cells were analysed by FACS (Section
3.5).
3.1.5 Treatment of Breast Cancer Cell Lines
3.1.5.1 MTS Proliferation Assay
To prepare cultures for MTS proliferation assays, MCF-7 cells were trypsinised and the
trypsin inactivated using RPMI/2%FCS/PS41 (Section 3.1.1). Cells were seeded into 96-
well plates at 1000 cells/well in 200 μL RPMI/2%FCS/PS41 and cultured for 1-2 days at
37ºC and 5% CO2. To commence treatment of the cells, 100 μL medium was removed
from each well and 100 μL RPMI/2%FCS/PS41 containing additives to give final
concentrations of 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12 and/or 2 μM
cyclopamine10 was added to the appropriate wells, with sextuplet wells prepared for
each treatment group. Every 2 days, 100 µL of the medium was replaced in each well.
For assessment of mitoxantrone effects on the cells, 100 μL medium was removed from
each well at day 4 of treatment and replaced with 100 μL of the appropriate medium
supplemented with mitoxantrone to obtain final concentrations of 0 µM, 0.0001 µM,
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65
0.001 µM, 0.01 µM, 0.1 µM, 1 µM, 3 µM, 5 µM or 10 μM mitoxantrone. The cells
were incubated for 4 days, with the medium replaced every 2 days, then cell numbers
were estimated using MTS proliferation assays (Section 3.2).
3.1.5.2 Immunofluorescence Microscopy
To culture cells for immunofluorescence microscopy, cleaned glass coverslips were
placed into 6-well plates and UV-sterilised for 20-30 minutes before 2 mL
RPMI/10%FCS/PS41 was added to each well and the plates incubated at 37ºC, 5% CO2
for ~2 h. MCF-7 cells were trypsinised (Section 3.1.1) and 4×105 cells were seeded onto
each coverslip. Plates were cultured at 37ºC and 5% CO2 for 1-2 days, medium was
changed to RPMI 1640 containing 5% charcoal-treated foetal calf serum (CSS) and
antibiotics (RPMI/5%CSS/PS)40 for 24 h, then the medium was replaced with 2 mL
RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2
μM cyclopamine10 or 10-8 M DHT and 2 μM cyclopamine. Cultures were incubated for
4 days prior to fixation and analysis by immunofluorescence microscopy (Section 3.3).
For staining of cells with the lysosome marker, Lysotracker Red, MCF-7 cultures grown
on glass coverslips in 6-well plates (as described above) were incubated with 50 nM
Lysotracker Red, prepared in 2 mL RPMI/5%CSS/PS40, for 20 minutes at 37ºC, 5%
CO2. Staining of Lysotracker Red was evaluated by immunofluorescence microscopy
(Section 3.3).
3.1.5.3 Flow Cytometry
To prepare cells for flow cytometric analysis of the intracellular levels of Rhodamine
123 or mitoxantrone, MCF-7 cells were trypsinised (Section 3.1.1), 2×105 cells were
added to 25 cm2 flasks and cultured in 5 mL RPMI/10%FCS/PS41 at 37ºC, 5% CO2 for
3-4 days or until cells had reached ~70% confluency. The cells were then incubated in 5
mL RPMI/10%FCS/PS41 containing 0.5 µg/mL Rhodamine 12338 or 1 µM mitoxantrone
for 60 minutes at 37ºC, 5% CO2. Culture medium was replaced with 5 mL
RPMI/10%FCS/PS41 and cells were cultured for 1-24 h prior to trypsinisation (Section
3.1.1). To investigate DHT and cyclopamine regulation of mitoxantrone intracellular
fluorescence, MCF-7 cells grown 25 cm2 flasks were incubated in RPMI/5%CSS/PS40
for 24 h before 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 µM cyclopamine10
or 10-8 M DHT and 2 µM cyclopamine was added. Culture media were replaced every 2
Chapter 3: Methods
66
days and after 8 days of treatment, the media were replaced with RPMI/5%CSS/PS40
containing the appropriate additives and 1 µM mitoxantrone. After a further 60 minutes
of incubation at 37ºC and 5% CO2, culture media were aspirated from the flasks and
replaced with RPMI/5%CSS/PS40 containing the appropriate additives but without
mitoxantrone for 60 minutes during which cells were trypsinised every 15 minutes. To
trypsinise cells for flow cytometry (Section 3.4), culture media were aspirated from the
culture flasks, cells were rinsed with ice-cold PBS32, then trypsinised (Section 3.1.1).
RPMI/5%CSS/PS40 was added to inactivate the trypsin and 1×106 cells were transferred
into Canto tubes. Tubes were centrifuged at 260 g for 5 minutes at 4ºC, the supernatants
were aspirated and the cell pellets were re-suspended in 500 μL ice-cold PBS32. Cell
suspensions were incubated on ice for 30 minutes with 5 µL 7-aminoactinomycin D (7-
AAD)2 which stains non-viable cells. The Canto tubes were again centrifuged at 260 g
for 5 minutes at 4ºC, the supernatants removed and the cell pellets re-suspended in 500
μL ice-cold PBS32 prior to flow cytometric analysis (Section 3.4).
3.1.5.4 Western Blotting
For preparation of cultures for western blotting, MCF-7 cells were trypsinised (Section
3.1.1), seeded into 6-well plates at 3×105 cells/well and incubated for 1-2 days in 2 mL
RPMI/10%FCS/PS41 at 37ºC, 5% CO2. The medium was then replaced with 2 mL
RPMI/5%CSS/PS40 and after 24 h, the culture medium was aspirated and cultures were
incubated in 2 mL RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control),
10-8 M DHT12, 2 μM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine. Cells were
harvested after 0-8 days of treatment for subcellular fractionation (Section 3.6) or
western blotting (Section 3.7).
For MG132 treatment of MCF-7 cells, cells were seeded at 3×105 cells/well into 6-well
plates and cultured for 1-2 days in 2 mL RPMI/10%FCS/PS41. The culture medium was
then replaced with 2 mL RPMI/5%CSS/PS40 and after 24 h, cultures were treated with
0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 μM cyclopamine10 or 10-8 M DHT
and 2 μM cyclopamine for 2 days prior to addition of 2 μM MG13228 and incubation for
a further 6 h. Cells were then lysed for western blotting (Section 3.7).
For chloroquine treatment of MCF-7 cells, cells were plated into 6-well plates at 1×105
cells/well in 2 mL RPMI/10%FCS/PS41, then culture medium was replaced with 2 mL
Chapter 3: Methods
67
RPMI/5%CSS/PS40 for 24 h and subsequently cells were cultured in 2 mL
RPMI/5%CSS/PS40 containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2
μM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine for 4 days. At day 4 of the
treatments, 25 μM chloroquine8 was added to the cultures, which were incubated for 6,
24 and 48 h prior to harvesting of the cells for western blotting (Section 3.7).
3.1.5.5 RNA Extraction
To extract RNA from MCF-7 and T-47D cells, cells were trypsinised (Section 3.1.1),
plated at 1:8 dilution into 100 mm petri dishes containing 10 mL RPMI/10%FCS/PS41
and cultured overnight at 37ºC, 5% CO2. The following day, culture medium was
changed to RPMI/5%CSS/PS40 for 24 h and then replaced with RPMI/5%CSS/PS40
containing 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12, 2 μM cyclopamine10 or
10-8 M DHT and 2 µM cyclopamine. RNA was isolated from cells after 24 h of
treatment (Section 3.8.1).
3.1.5.6 Wound Healing Assays
For evaluation of MCF-7 cell migration by wound healing assays, cells were trypsinised
(Section 3.1.1), seeded into 100 mm petri dishes at 4×105 cells/dish and cultured in 10
mL RPMI/10%FCS/PS41 for 1-2 days. Culture medium was then replaced with 10 mL
RPMI/2%FCS/PS41 and after 24 h, 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT12,
2 µM cyclopamine10 or 10-8 M DHT and 2 µM cyclopamine was added to the dishes and
cells were cultured for 4 days with the medium replaced every 2 days. A sterile pipette
tip was used to create wound areas by scratching the cell monolayer, then culture
medium was replaced to remove non-adherent cells. Cell migration into the wound
areas was quantitated by capturing images of the wound areas at 0, 24, 48 and 72 h of
treatment using a Nikon Eclipse TS1000 phase contrast microscope equipped with a
Tucsen® IS500 camera and ISCapture software, and the percentages of wound area
covered by cells were calculated using TScratch. The rate of wound closure was
obtained by determining the wound widths at times 0, 24, 48 and 72 h, calculating the
difference in wound widths between time 0 (time=0) and each of the later timepoints,
then dividing these differences by the wound width at t=0 (×100 = % wound closure).
Chapter 3: Methods
68
3.1.5.7 BioCoat™ Matrigel™ Invasion Assays
Assays using BioCoat™ Matrigel™ Invasion Chambers were performed according to the
manufacturer’s protocol. Briefly, BioCoat™ Matrigel™ Invasion Chambers were thawed
in 24-well plates for 15 minutes at room temperature to allow the Matrigel™ to gel and
subsequently transferred to wells containing 500 µL RPMI/5%CSS/PS40. 500 µL
RPMI/5%CSS/PS40 was then added to the chambers and the plates were incubated at
37ºC, 5% CO2 for ≥2 h to equilibrate the Matrigel™. MCF-7 cells were trypsinised, the
trypsin inactivated by addition of RPMI/2%FCS/PS41 (Section 3.1.1), and to seed 5×104
cells/chamber, 1 mL suspensions of cells containing 10×104 cells were prepared in
RPMI/2%FCS/PS41. Medium in the chambers was aspirated, the chambers were
transferred to wells containing 750 µL RPMI/10%FCS/PS41 which had been pre-
incubated at 37ºC, 5% CO2 for ~2 h, 500 µL of the cell suspension was added to each
chamber and the plates were incubated for 24 or 48 h. To stain the cells that had invaded
through the Matrigel™ and the underlying filter into the lower chamber of the plate,
medium was removed from the chamber and using a cotton swab, the upper surface of
the membrane was scrubbed to remove the Matrigel™ and cells that had not invaded
through the Matrigel™ layer. Cells that had invaded through the Matrigel™ to the under-
side of the filter were stained in 24-well plates by incubating the membrane in 500 µL
100% methanol for 2 minutes, 500 µL 1% Toluidine blue O53 for 10 minutes, then 2× 2
minutes in 1mL ddH2O. Cotton swabs were used to remove excess debris and moisture
from the upper membrane surface and each membrane was excised from the chamber
using a surgical blade, placed onto a drop of immersion oil on microscope slides,
covered with a glass coverslip and sealed using clear nail polish. Filters were imaged
using an Olympus BX43 microscope equipped with cellSens™ software and numbers of
cells were counted manually.
3.1.5.8 3D Matrigel™ Colony Formation Assays
To investigate MCF-7 cell invasion by 3D Matrigel™ colony formation assays, growth
factor reduced Matrigel™ was thawed on ice for 1-2 h, then 200 µL Matrigel™ per well
was added to 24-well plates, which were incubated at 37ºC, 5% CO2 for ≥30 minutes to
coat the wells with Matrigel. MCF-7 cells were trypsinised, the trypsin was inactivated
with RPMI/2%FCS/PS41 (Section 3.1.1) and aliquots of 1×104 cells in 1.5 mL
microcentrifuge tubes were centrifuged at 260 g for 5 minutes at 4ºC. Supernatants were
aspirated and cell pellets were re-suspended in 300 µL Matrigel™ containing 0.1% (v/v)
Chapter 3: Methods
69
ethanol (vehicle control), 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM
cyclopamine. The cell suspensions were immediately added to the Matrigel™-coated
wells and cultures were incubated at 37ºC and 5% CO2 for ~30 minutes to allow the
Matrigel™ to gel. 200 µL RPMI/2%FCS/PS41 containing the appropriate treatments
(0.1% (v/v) ethanol, 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM
cyclopamine) was added to the Matrigel™ cultures and the plates were cultured for 10
days, with culture medium replaced every 2 days. At the end of the treatment period,
images of colonies were captured in 10 fields per well using a Nikon Eclipse TS1000
phase contrast microscope equipped with a Tucsen® IS500 camera and ISCapture
software. Colony size was quantitated using Image J by measuring the number of pixels
occupied by each colony.
3.2 MTS Proliferation Assays
MTS proliferation assays were performed using a CellTiter 96® AQueous One Solution
Kit according to manufacturer’s protocol. Briefly, 100 μL culture medium was removed
from each well of 96-well plates (Section 3.1.5.1) and replaced with 20 μL MTS
reagent. The culture plates were incubated at 37ºC for 4 h protected from light and the
absorbance of formazan generated from MTS by viable cells was measured at 490 nm
using a UVM 340 microplate reader equipped with KIM software. Absorbance values
from blank wells, which did not contain cells, were subtracted from experimental wells
and cell numbers were extrapolated from a standard curve. To prepare standard curves,
cells were seeded at 250 to 30,000 cells per well in quadruplicate wells in 96-well plates
and incubated at 37ºC, 5% CO2 for 20-24 h prior to analysis by MTS assay. Mean
absorbance values were plotted against cell density and a linear trend line was fitted
through the values. To calculate cell numbers from standard curves, the linear
regression equation y=mx+c (y: absorbance, x: cell number) was used. Mitoxantrone
dose-response curves were constructed in Prism®, with IC50 values for mitoxantrone or
dose of mitoxantrone required for 50% inhibition of cell proliferation extrapolated from
the dose-response curves.
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70
3.3 Immunofluorescence Microscopy
To prepare MCF-7 cells cultured on coverslips for immunofluorescence microscopy
(Section 3.1.5.2), medium was removed from 6-well plates, cells were rinsed twice with
1-2mL PBS32 and then incubated at room temperature with 4% formaldehyde22 for 15
minutes. Cells were washed for 3× 5 minutes with PBS32, permeabilised in 0.2% (v/v)
Triton-X 10061 for 5 minutes, washed for 3× 5 minutes with PBS32 and then incubated
for 30 minutes in Blocking Buffer4. After blocking, cells were washed 3× 5 minutes
with PBS32, then incubated overnight at 4ºC with the ABCG2 primary antibody diluted
at 1:500 (v/v) in PBS/1% BSA34, in humidified containers. The following day, cells
were rinsed for 5× 5 minutes with PBS32 at room temperature, after which all
procedures were performed in minimal light. Cells were incubated for 90 minutes with
the cell nuclear stain, Hoechst 33258 diluted at 1:4000 (v/v) in PBS/1% BSA34 and
Alexafluor® 488- or Alexafluor® 546-conjugated anti-mouse secondary antibodies
which were diluted at 1:400 (v/v) in PBS/1% BSA34. Cells were rinsed 3× 5 minutes
and then incubated for 45 minutes with Phalloidin Red36 diluted at 1:2000 (v/v) in
PBS/1% BSA33 or with 0.1% (v/v) DMSO diluted in PBS/1% BSA34 for cells not
stained with Phalloidin Red. Cells were rinsed with PBS32 for 5× 5 minutes before
coverslips were mounted on microscope slides using Mounting Medium29 and the edges
of the coverslips sealed using nail polish. Slides were stored at 4ºC prior to imaging
with a Nikon Eclipse Ti-e fluorescence microscope or a Nikon A1 confocal microscope.
Hoechst 33258 (excitation, 346 nm; emission, 460 nm), and Alexafluor® 488 (green)
(excitation, 488 nm; emission, 519 nm) were detected using DAPI and FITC filters,
respectively, whereas Phalloidin Red (excitation, 540 nm; emission, 565 nm),
Alexafluor® 546 (red) (excitation, 561 nm; emission, 572 nm) and Lysotracker Red
(excitation, 577 nm; emission, 590 nm) were detected using TRITC filters. Using the z-
stack feature in the image acquisition software, NIS-Elements™, 10-11 images at an
optical thickness of 0.5 μm per image that were serially captured from the top to the
bottom of cells were merged using AutoQuant X3. Images were coloured using Adobe®
Photoshop CS.
3.4 Flow Cytometry
Intracellular levels of Rhodamine 123 and mitoxantrone were evaluated using a BD
FACSCanto™ II flow cytometer equipped with BD FACSDiva 6.0 software. 7-AAD
Chapter 3: Methods
71
and Rhodamine 123 fluorescence signals were detected by a blue laser excitation source
(488 nm) and emission filters were 650 nm long pass for 7-AAD and 530/30 nm band
pass for Rhodamine 123. Mitoxantrone fluorescence was excited by a red laser (635
nm) and signals were detected by a 670/30 nm bandpass emission filter. MCF-7 cells
prepared for flow cytometry (Section 3.1.5.3) were dispersed by passing through a 23 G
needle and 1 mL syringe prior to flow cytometric analysis. Geometric mean of
fluorescence intensities (MFIs) of Rhodamine 123 and mitoxantrone were determined
using Flowjo.
3.5 Fluorescence-Activated Cell Sorting (FACS)
Following staining of MCF-7 cells with Hoechst 33342, CD44-APC and CD24-PE
antibodies (Section 3.1.4), breast cancer stem-like cells which accumulate low levels of
Hoechst 33342 (Hoechst 33342lo), due to elevated expression of ABC transporters (Kim
et al 2002, Patrawala et al 2005, Engelmann et al 2008, Yin et al 2008), and express
high levels of CD44 and low levels of CD24 (CD44hi/CD24lo) (Al-Hajj et al 2003) were
isolated from MCF-7 cells using a BD Influx™ Cell Sorter. Hoechst 33342 was excited
using an ultraviolet (UV) laser (350 nm) with Hoechst-blue signals detected by a 450/50
nm bandpass filter and Hoechst-red signals detected by a 675/50 nm bandpass filter.
CD44-APC was detected using a 660/20 nm emission filter following excitation by a
red laser (650 nm), and to detect CD24-PE, a blue laser excitation source (488 nm) and
575/26 nm emission filter were used. CD24-BV421 was detected using a purple laser
(405 nm) and a 450/50 nm bandpass filter. Prior to analysis of MCF-7 cells using the
BD Influx™ Cell Sorter, cell clumps were removed by passing the cell suspension
through Falcon™ tubes with cell strainer caps containing 35 µm nylon mesh. Isolated
breast cancer stem-like cells were seeded at 5000 cells/well into 24-well plates for
immunoblotting (Section 3.7) or onto glass coverslips, which had been UV-sterilised
and placed into 6-well plates, for immunofluorescence microscopy (Section 3.3). Cells
were cultured in 1-2 mL RPMI/10%FCS/PS41 for 3-4 days before culture medium was
replaced with RPMI/5%CSS/PS40. After 24 h, RPMI/5%CSS/PS40 containing a final
concentration of 0.1% (v/v) ethanol, 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT
and 2 µM cyclopamine was added to cultures. For immunoblotting (Section 3.7), cells
were treated for 8 days and for immunofluorescence microscopy (Section 3.3), cells
were treated for 4 days.
Chapter 3: Methods
72
3.6 Subcellular Fractionation
For subcellular fractionation, cells cultured in 6-well plates (Section 3.1.5.4) were
placed on ice, medium was aspirated from the wells, the cells were rinsed with 1-2 mL
ice-cold PBS32 and 400 μL cell lysis buffer7 was added to each well. Cells were scraped
using a rubber policeman, collected into pre-chilled 1.5 mL microcentrifuge tubes then
incubated on ice for 20 minutes with vigorous pipetting of the lysates every 5 minutes to
enhance cell lysis. Cell nuclei were pelleted by centrifugation at 2320 g for 5 minutes at
4ºC and the supernatants, which contained cytoplasmic proteins, were transferred into
pre-chilled 1.5 mL microcentrifuge tubes then stored at -20ºC. Cell pellets were rinsed
in 400 μL ice-cold PBS32, tubes were centrifuged at 2320 g for 5 minutes at 4ºC and
supernatants were discarded. Pellets were resuspended in 250 μL nuclear lysis buffer30,
the solution sonicated for 4× 15 seconds on ice, centrifuged at 14,500 g, 4ºC for 10
minutes and the supernatants containing nuclear proteins were transferred into pre-
chilled 1.5 mL microcentrifuge tubes and stored at -20ºC. The remaining pellets, which
contained cell membranes and vesicles which had not been lysed were collected in
whole cell lysis buffer64 and stored at -20ºC.
3.7 Western Blotting
3.7.1 Whole Cell Lysis
Lysis of cells as whole cell extracts for western blotting was performed at room
temperature in a fume cupboard. MCF-7 cells cultured in 6-well plates (Section 3.1.5.4)
were rinsed with 1-2 mL PBS32 and 250-600 µL whole cell lysis buffer64 was added to
each well. Breast cancer stem-like cells cultured in 24-well plates (Section 3.5) were
rinsed with 1 mL PBS32 and lysed in 100-200 µL whole cell lysis buffer64. Cells were
scraped into 1.5 mL microcentrifuge tubes using a rubber policeman, and cell lysates
were repeatedly passed through a 23 G needle and 1 mL syringe to reduce viscosity,
then stored at -20ºC or analysed by SDS-polacrylamide gel electrophoresis (SDS-
PAGE) (Section 3.7.2) and immunoblotting (Section 3.7.3).
3.7.2 SDS-Polyacrylamide Gel Electrophoresis (SDS-PAGE)
SDS-PAGE was performed using a Mini Protean® Tetra Cell (BioRad) according to the
manufacturer’s protocol. Briefly, 12% separating gel mixture43 was prepared and poured
Chapter 3: Methods
73
between glass gel plates until ~0.5 cm below the level of the wells, the gel solution was
overlayed with ddH2O and the gel incubated at room temperature for 45-60 minutes to
polymerise. Following removal of ddH2O, 4% stacking gel mixture48 was prepared and
poured over the separating gels, well combs were inserted and the gels were left to
polymerise at room temperature for 30-45 minutes. Prepared gels were assembled into
the apparatus in tanks containing 1× western running buffer63.
In preparation for SDS-PAGE, 15-20 μL cell lysates were combined with appropriate
volumes of 10× western loading buffer62, heated at 95ºC for 5-7 minutes, allowed to
cool to room temperature then loaded into the wells. A well containing 5 μL Colour
Plus® pre-stained protein marker was included in each gel, and gels were
electrophoresed at 200 V for ~1 h. Following electrophoresis, gels were removed from
the glass casting plates, stacking gels removed and the separating gels placed into cold
transfer buffer58. All transfer components were similarly pre-soaked in cold transfer
buffer58. From the negative electrode (black) of the transfer cassettes, transfer
sandwiches were assembled with a scotch brite, 2× filter paper, the gel, nitrocellulose
filter, 2× filter paper and a scotch brite. The transfer cassettes were closed, placed into
transfer tanks containing cold transfer buffer58 and proteins were transferred overnight
at 30V and at room temperature.
3.7.3 Immunoblotting
For immunoblotting, nitrocellulose membranes were blocked in Tris-buffered saline
(TBS) containing 3% skim milk powder (TBS/3% Blotto56) for 90 minutes at room
temperature, then incubated with primary antibodies diluted in TBS containing Tween-
20 (TBST)55 and 1% skim milk powder (TBST/1% Blotto57) either overnight at 4ºC for
ABCG2 immunoblots or at room temperature for 90 minutes for AR and β-actin
immunoblots (Table 3.1). Following primary antibody incubation, nitrocellulose
membranes were washed at room temperature with TBST55 for 3× 10 minutes and
incubated at room temperature with the appropriate secondary antibodies diluted in
TBST/1% Blotto57 for 90 minutes (Table 3.1). Nitrocellulose membranes were washed
with TBST55 for 3× 10 minutes, incubated with Enhanced Chemiluminescence (ECL)
reagent17 for 5 minutes then wrapped in cling wrap, exposed to X-ray film for 10
seconds to 5 minutes as required and the films developed using an Agfa CP1000
developer. Films were scanned using an HP2500 Precision document scanner and
Chapter 3: Methods
74
quantitated using Quantity One® software, with levels of proteins of interest normalised
against corresponding β-actin levels from the same lanes and expressed as a proportion
of vehicle controls where appropriate.
Table 3.1: Antibody Dilutions for Immunoblotting
Primary Antibodies Mouse anti-human ABCG2 1:750 Mouse anti-human AR 1:1000 Goat anti-human β-actin 1:3000
Secondary Antibodies Anti-mouse IgG Anti-goat IgG
1:10,000 1:30,000
3.8 Polymerase Chain Reaction (PCR) and Reverse Transcription
Quantitative PCR (RT-qPCR)
3.8.1 RNA Extraction
RNA was extracted from cells using an RNeasy® Mini Kit according to manufacturer’s
protocol. For RNA extraction from cell pellets, cells grown in petri dishes (Section
3.1.5.5) were trypsinised (Section 3.1.1) then 8-9 mL RPMI/5%CSS/PS40 was added to
inactivate the trypsin, the cell suspensions were transferred to 10mL tubes which were
centrifuged at 260 g for 5 minutes at room temperature, supernatants were aspirated and
the cell pellets were stored at -80ºC. To lyse cells in pellets, the appropriate volume of
Buffer RLT for RNA extraction (350 μL Buffer RLT for <5×106 cells or 600 μL Buffer
RLT for 5×106-1×107 cells) was added to the pellets and the suspensions were
transferred to 1.5 mL microcentrifuge tubes. For direct lysis of cells, culture medium
was removed from petri dishes (Section 3.1.5.5), 600 μL Buffer RLT was added and
cells were scraped using a rubber policeman and collected into 1.5 mL microcentrifuge
tubes.
Following cell lysis, viscosity of the lysates was reduced by passing the solution
repeatedly through a 23 G needle and 1mL syringe, an equal volume of 70% ethanol19
was added to each lysate and the solution transferred to RNeasy® spin columns in 2 mL
Chapter 3: Methods
75
collection tubes, which were centrifuged at 8000 g for 15 seconds at room temperature.
The flow-throughs were discarded and 350 μL Buffer RW1 was added to each of the
spin columns, which were again centrifuged for 15 seconds at 8000 g and room
temperature and flow throughs discarded. For DNase treatment, 10 μL 2.72 kunitz
units/µL DNase13 was combined with 70 μL Buffer RDD, and the solution added
directly to the spin columns, which were incubated at room temperature for 15 minutes.
350 μL Buffer RW1 was added to the spin columns, the columns were centrifuged at
8000 g for 15 seconds and flow throughs were discarded. The spin columns were
washed twice with 500 μL Buffer RPE, with the columns centrifuged at 8000 g for 15
sec after the first wash and for 2 minutes following the second wash. The columns were
then transferred to fresh 2 mL collection tubes, centrifuged again at 8000 g for 1 minute
and then placed into sterile 1.5 mL microcentrifuge tubes. To elute RNA, 30-50 μL
RNase-free water was added to the columns, the columns were centrifuged for 1 minute
at 8000 g and RNA was stored at -80ºC.
3.8.2 Reverse Transcription
cDNA synthesis for RT-qPCR assays was performed using Superscript™ III, whereas a
RT2 First Strand cDNA Synthesis Kit was used to prepare cDNA for RT2 Profiler PCR
Arrays.
3.8.2.1 cDNA Synthesis Using Superscript™ III
To synthesise cDNA using Superscript™ III, 1 μL 500 µg/mL oligo(dT), 1 μg RNA and
1 μL 10 mM dNTP16 were combined in a 0.2 mL microcentrifuge tube and made up to
14 μL with ddH2O. The solution was then heated at 65ºC for 5 minutes, immediately
incubated on ice for at least 1 minute and a master mix containing 4 μL 5× First-Strand
Buffer, 1 μL 0.1M DTT and 1 μL Superscript™ III was added to each tube. The mixture
was combined by pipetting, incubated at 50ºC for 60 minutes, then at 70ºC for 15
minutes to inactivate the enzyme.
3.8.2.2 Preparation of cDNA Using the RT2 First Strand cDNA Synthesis Kit
For synthesis of cDNA using the RT2 First Strand Kit, a genomic DNA (gDNA)
Elimination Mixture was prepared by combining 1 μg RNA, 2 μL Buffer GE and the
solution was made up to 10 µL with ddH2O. The solution was mixed by pipetting,
incubated at 42ºC for 5 minutes and placed on ice for ≥1 minute. An RT cocktail
Chapter 3: Methods
76
containing 4 μL Buffer BC3, 1 μL Buffer P2, 2 μL Buffer RE3 and 3 μL ddH2O was
prepared, added to each sample and the solution combined by pipetting. Tubes were
again incubated at 42ºC for 15 minutes and the reaction was terminated by incubation at
95ºC for 5 minutes. cDNA samples were diluted with 91 μL RNase-free water or stored
overnight at -20ºC.
3.8.3 Purification of cDNA
cDNA samples were purified at room temperature using a QIAquick® PCR purification
kit as described in the manufacturer’s protocol. Briefly, five volumes of Buffer PB was
added to each cDNA, and the solution was added to QIAquick® spin columns in 2 mL
collection tubes, which were centrifuged for 30-60 seconds at 12,000 g. The flow
throughs were discarded and the columns were washed by addition of 750 μL Buffer PE
and centrifugation for 30-60 seconds at 12,000 g. The flow throughs were removed and
the columns were again centrifuged for 30-60 seconds at 12,000 g to remove residual
Buffer PE. To elute the cDNA, the spin columns were transferred into clean 1.5 mL
microcentrifuge tubes, 40-50 μL Buffer EB was added to each column, the columns
were incubated at room temperature for 1 minute, then centrifuged for 30-60 seconds at
12,000 g. Purified cDNA was stored at -20ºC.
3.8.4 Primer Design
Primer sequences for ABCG2 were obtained from a previous study (Nakanishi et al
2003), while primers for the AR and reference genes, GAPDH and β-actin were
designed using Primer-BLAST (Ye et al 2012) and checked using Oligo Calc (Kibbe
2007) (Table 3.2).
3.8.5 Polymerase Chain Reaction (PCR)
To prepare 25 μL PCRs, 5 µL 5× PCR buffer35, MgCl227 (Table 3.2), 15 ρmol sense and
anti-sense primers (Table 3.2), 0.1 µL 5 U/µL Platinum® Taq DNA polymerase and
ddH2O (final reaction volume 25 µL) were prepared as a master mix and added to 0.2
mL microcentrifuge tubes. 10 ng cDNA was added to the appropriate tubes and PCR
amplification was performed in C1000™ Thermal Cyclers as follows:- 95ºC/4 minutes,
then 35 cycles of (i) 95ºC/30 seconds, (ii) 60-65ºC/30 seconds (Table 3.2), (iii) 72ºC/1
minute, and a final elongation step of 72ºC for 4 minutes. Each PCR run included a
Chapter 3: Methods
77
negative control, which did not contain cDNA. Following amplification, PCR products
were analysed by agarose gel electrophoresis (Section 3.8.6) or stored at -20ºC.
3.8.6 Agarose Gel Electrophoresis
To prepare gels for agarose gel electrophoresis, 2% (w/v) agarose1 was heated in a
microwave to melt the agarose, cooled at room temperature to ~70ºC, the solution
poured into casting trays containing gel combs and the gel incubated at room
temperature for 45-60 minutes to solidify. For electrophoresis, 5-10 µL PCR products
(Section 3.8.5) were combined with the appropriate volume of 6× DNA loading buffer15
and added to wells. Each gel contained a lane with 5 µL 1kb Plus DNA ladder™ 14. Gels
were electrophoresed in 1× TAE buffer52 at room temperature for ~30 minutes at 100 V.
Following electrophoresis, gels were visualised using a BioRad Gel Doc 2000EQ with
Quantity One® software.
3.8.7 Reverse Transcription-Quantitative PCR (RT-qPCR)
For RT-qPCR, 20 μL reactions contained 2× GoTaq® qPCR master mix, 4 ρmol sense
and anti-sense primers (Table 3.2), 2 ng cDNA and ddH2O. qPCR was performed in 0.2
mL tubes in a Rotorgene-6000 as follows:- 95ºC/5 minutes, then 40 cycles of (i)
95ºC/15 seconds, (ii) 60-65ºC/30 seconds (Table 3.2), then 95ºC/1 minute, 40ºC/1
minute and a melt curve from 58ºC to 95ºC at a ramp rate of 0.5ºC/sec. Negative
controls, which did not contain cDNA, and efficiency curves for target and reference
genes were included in every qPCR. To construct efficiency curves, qPCRs containing
serial dilutions of 2ng cDNA were prepared and following PCR amplification, mean
threshold cycle (Ct) values were plotted against log cDNA concentration in Excel, a
linear curve was fitted through the points and the slope (m) of the linear curve from the
linear regression equation (y=mx+c) was used to calculate the amplification efficiency
(E).
E: 10-1/slope
For calculation of relative expression of target genes, mean Ct values for target and
reference genes were obtained and the following Pfaffl equation was used:
Ratio: (Etarget) ∆Ct target (control-sample)/ (Eref) ∆Ct ref (control-sample)
Etarget and Eref refer to amplification efficiencies for target and reference genes,
respectively, whereas ∆Ct target or ref (control-sample) is the difference in Ct values of
Chapter 3: Methods
78
target or reference genes between control (e.g. vehicle control) and experimental
samples.
Table 3.2: Primers for PCR and RT-qPCR
Gene Primer Sequences Annealing Temperature
Amplified PCR
product (bp)
MgCl2 (mM)
ABCG2
Sense: 5’-GTT TCA GCC GTG GAA CTC TTT G-3’ Anti-sense: 5’-GCA TCT GCC TTT GGC TTC AAT-3’
60ºC 191 3.5
AR
Sense: 5’-CCT GGC TTC CGC AAC TTA CAC-3’ Anti-sense: 5’-GGA CTT GTG CAT GCG GTA CTC A-3’
65ºC 168 3
β-actin
Sense: 5’-GCT GAT CCA CAT CTG CTG GAA-3’ Anti-sense: 5’-ATT GCC GAC AGG ATG CAG AA-3’
60ºC 150 2
GAPDH
Sense: 5’-TGA GGT CAA TGA AGG GGT C-3’ Anti-sense: 5’-GTG AAG GTC GGA GTC AAC G-3’
60ºC 112 2
3.8.8 PCR Arrays
In this study, high-throughput screening of EMT-associated genes in MCF-7 and T-47D
cells was performed using RT2 Profiler Human EMT PCR Arrays according to the
manufacturer’s protocol. The arrays contained optimised primers for analysis of 84
EMT-associated genes, five housekeeping genes (β-actin (ACTB), beta-2-microglobulin
(B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hypoxanthine
phosphoribosyltransferase 1 (HPRT1) and ribosomal protein large, P0 (RPLP0)), a
human genomic DNA control (HGDC), reverse transcription controls (RTC) and PCR
positive controls (PPC) (Figure 3.1, Appendix 2). To prepare cDNA for the PCR arrays,
RNA extracted from MCF-7 and T-47D cells treated for 24 h with 0.1% (v/v) ethanol
(vehicle control), 10-8 M DHT12, 2 µM cyclopamine10 or 10-8 M DHT and 2 µM
cyclopamine (Section 3.8.1), was reverse transcribed (Section 3.8.2.2), added to 550 µL
2× RT2 SYBR green master mix and made up to 1100 µL with RNase-free ddH2O. The
solution was mixed by pipetting then 10 μL per well was loaded into the PCR array
1
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79
Chapter 3: Methods
80
plates using a Corbett liquid handling robot and conductive tips (Figure 3.2). The array
plates were sealed with optical adhesive films, centrifuged at 1620 g for 7-10 seconds at
room temperature and qPCR performed in a Light Cycler® 480 as follows:- 95ºC/10
minutes with a ramp rate of 4.8ºC/second, then 45 cycles of (i) 95ºC/15 seconds with a
ramp rate of 1ºC/second and (ii) 60ºC/1 minute with a ramp rate of 1ºC/second. This
was followed by a final incubation at 60ºC for 15 seconds with a ramp rate of
4.8ºC/second, then a melt curve with increase of the temperature to 95ºC at a ramp rate
of 0.03ºC/second in continuous acquisition mode. Ct values were obtained and uploaded
to the SABiosciences web-based data analysis program at
http://www.sabiosciences.com/dataanalysis.php using downloadable Excel templates.
Figure 3.2: Loading of 384-well RT2 Profiler PCR Arrays (G Format). cDNA (10 µL per well) from each of the MCF-7 and T-47D treatment groups (1: 0.1% (v/v) ethanol, 2: 10-8 M DHT, 3: 2 μM cyclopamine, 4: 10-8 M DHT + 2 μM cyclopamine) was loaded into the wells as indicated (according to the manufacturer’s protocol).
3.9 Sanger Sequencing
Sequencing reactions each contained 8 µL 2.5× buffer, 0.5 µL Big Dye® Terminator
(BDT), ddH2O (prepared as a master mix), 4 ng purified PCR products (Section 3.8.3,
3.8.5) and 3 ρmol sense or anti-sense primer (Table 3.2). Sequencing was performed in
C1000™ Thermal Cyclers under the following cycling conditions: 25 cycles of (i)
95ºC/15 seconds, (ii) 60ºC/10 seconds, (iii) 60ºC/4 minutes. To precipitate sequencing
reactions, 50 µL 95% ethanol19 and 2 µL sodium acetate44 were added to each reaction,
the tubes vortexed, incubated on ice for 10 minutes and centrifuged at 16,168 g for 30
minutes at 4ºC. Supernatants were removed using a pipette, 250 µL 70% ethanol19 was
added to each tube, and the tubes were centrifuged at 16,168 g for 5 minutes at 4ºC.
Supernatants were again removed using a pipette and pellets were air dried at room
Chapter 3: Methods
81
temperature for 15 minutes. Sequencing was performed using 3730 DNA analysers and
sequencing chromatograms were viewed using Chromas Lite software and analysed
using BLAST® (Mount 2007).
Chapter 4
DHT AND CYCLOPAMINE EFFECTS ON THE
EXPRESSION AND FUNCTION OF ABCG2 IN
MCF-7 AND T-47D CELLS
Chapter 4
82
4.1 Introduction
Breast cancer growth is regulated by a number of signalling pathways and their
interaction facilitates progression of the disease to cancers of poorer prognosis. The
androgen receptor (AR) is expressed in 70-90% of breast tumours and is generally
associated with better disease prognosis and longer overall survival of patients, while
the Hedgehog signalling pathway is hyperactivated in breast cancer cells and breast
tumours (Kubo et al 2004, Gonzalez et al 2008). Androgens (e.g. testosterone, 5α-
dihydrotestosterone (DHT)) and Sonic Hedgehog (SHH) activate their respective AR
and Hedgehog signalling pathways, resulting in the regulation of cell proliferation, cell
survival, differentiation and motility (Section 1.4.4, 1.4.5). This occurs via
transcriptional regulation of target genes that encode mediators of cell survival
pathways and physiological processes such as the cell cycle (Bonifas et al 2001, Bolton
et al 2007). Cross-talk between the AR and Hedgehog signalling pathways has been
reported previously, with the AR shown to directly interact with the Hedgehog/GLI
transcription factors leading to reciprocal regulation of expression of target genes
between the two pathways (Chen et al 2011a, Sirab et al 2012a). Findings from a more
recent study using prostate cancer cells also provided evidence that combined targeting
of the AR and Hedgehog signalling pathways may improve therapeutic outcomes where
cancers exhibit active AR and Hedgehog signalling (Gowda et al 2013).
The ABC drug efflux transporters are major contributors to the development of drug
resistance and treatment failure in breast cancer, and overexpression of the transporters
in tumours has been associated with elevated efflux of therapeutic agents (e.g.
chemotherapeutic drugs) from cancer cells (Kruijtzer et al 2002, Burger et al 2003,
Robey et al 2007, Kathawala et al 2015). ABCB1 and ABCG2, in particular, have been
extensively studied for their roles in the development of chemoresistance and in a small
sub-population of cancer cells termed cancer stem cells (Lou and Dean 2007, Ding et al
2010, Jiang et al 2012). Cancer stem cells have been identified in many tumour types
including blood cancers (e.g. acute myeloid leukaemia (AML)) and solid tumours (e.g.
breast tumours) (Lapidot et al 1994, Al-Hajj et al 2003). These cells exhibit
characteristics of tissue stem cells including quiescence (slow cell division), self-
renewing capabilities and the ability to differentiate into multiple cell lineages
(pluripotency) (Dontu et al 2003). As such, cancer stem cells are capable of undergoing
symmetrical division to give rise to two daughter cancer stem cells or asymmetrical
Chapter 4
83
division to “differentiate” into the majority of cancer cells which form the tumour bulk.
Although only a small subpopulation (<1%) of cancer cells exhibit characteristics of
cancer stem cells, these cells can promote tumour relapse, disease progression, drug
resistance and metastasis (Visvader and Lindeman 2008, Han et al 2013). Therefore,
development of therapeutic approaches to control or eliminate cancer stem cells may
provide a more effective strategy in the management of cancers and improve
progression-free and overall survival of patients.
Cancer stem cells may be identified by appropriate expression of cell surface markers
such as CD44 and CD24 in breast and pancreatic tumours, CD133 (breast, brain and
other cancers), and CD34 and CD38 in acute myeloid leukaemia (AML) cells (Lapidot
et al 1994, Al-Hajj et al 2003, Singh et al 2004). In human breast tumours, cells which
express high levels of CD44, low levels of CD24 and absence of Lineage markers (Lin-
ve) (CD44hi/CD24lo/Lin-ve) are enriched in breast cancer stem cells (Al-Hajj et al 2003).
CD44hi/CD24lo/Lin-ve cells were shown to exhibit a 10 to 50 fold increase in the
capacity to develop tumours compared to other non stem-like cells (e.g.
CD44hi/CD24hi/Lin-ve cells) when transplanted into NOD/SCID mice, re-capitulating the
heterogeneous population of cancer cells in the original tumour and thereby indicating
stem-like differentiation of the CD44hi/CD24-ve/lo/Lin-ve cells into multiple cell lineages
(Al-Hajj et al 2003).
Although expression of CD44 and CD24 are sound markers for breast cancer stem cells,
a combination of additional markers may be more reliable in the purification of breast
cancer stem cells (Ginestier et al 2007, Croker et al 2009). Cells with high aldehyde
dehydrogenase (ALDH) activity have been reported to contain stem/progenitor-like
properties such as an increased ability to form tumours in vivo (Hess et al 2004,
Ginestier et al 2007). Culture of ALDHhi cells isolated from normal human breast and
from human breast carcinomas formed mammospheres in suspension cultures and when
transplanted into the mammary fat pad of NOD/SCID mice, ALDHhi but not ALDHlo
cells formed tumours, indicating their tumorigenic potential (Ginestier et al 2007).
CD44hi/CD24lo breast cancer stem-like cells are reported to include both ALDHhi and
ALDHlo cells, and ALDHhi/CD44hi/CD24lo cells, but not ALDHlo/CD44hi/CD24lo cells
were capable of forming tumours in mice (Ginestier et al 2007, Croker et al 2009).
Chapter 4
84
These studies therefore indicated that a combination of CD44 and CD24 expression and
ALDH activity may more reliably distinguish breast cancer stem cells.
Expression of the ABC transporters has been implicated in maintaining cancer stem cell
growth. In MCF-7 cells which were selected for resistance to doxorubicin (MCF-
7/MDR), elevated expression of ABCB1 was associated with increased proportions of
CD44hi/CD24lo cancer stem-like cells compared to parental (unselected) MCF-7 cells
(Calcagno et al 2010). Cancer stem-like cells have been isolated from a number of
malignancies including breast, lung and pancreatic cancers via flow cytometric
identification of cells with low intracellular levels of the fluorescent ABC transporter
substrate, Hoechst 33342 (Kim et al 2002, Patrawala et al 2005, Engelmann et al 2008,
Yin et al 2008). These cells constitute a small subpopulation of cancer stem cells termed
“side population” (SP) cells which overexpress the ABC transporters, ABCB1 and
ABCG2, and are enriched for stem cell characteristics (Ho et al 2007, Wang et al
2009b, Calcagno et al 2010).
Culture of SP cells in suspension cultures resulted in formation of floating
mammospheres, a stem-like characteristic that was not evident in cultures of non-SP
cells (Hoechst 33342hi) (Engelmann et al 2008). SP but not non-SP cells were also
capable of differentiation into mixed populations of cells (Hoechst 33342hi and Hoechst
33342lo) following long term culture, and transplantation of SP cells into NOD/SCID
mice resulted in formation of tumours, supporting the tumorigenic potential and stem-
like properties of these cells (Patrawala et al 2005, Yin et al 2008). SP cells isolated
from the MCF-7 breast cancer cell line are reported to constitute ~7.5% of the total cell
population and a high proportion of these cells (~80%) were CD44hi and CD24lo,
providing strong evidence that the population was enriched for stem-like cells
(Engelmann et al 2008). As the ABC transporters are able to export chemotherapeutic
drugs (e.g. mitoxantrone, doxorubicin), their increased expression in cancer stem cells is
likely to contribute to the proposed role of this cancer cell subpopulation in the
development of drug resistance and tumour relapse (Lou and Dean 2007, Robey et al
2007, Visvader and Lindeman 2008).
A number of regulators of ABCG2 transcription, post-translational modification and
trafficking to the plasma membrane or other cellular compartments have been identified
Chapter 4
85
and these processes contribute to the synthesis of mature transporters that are
functionally active (Section 1.6.3.2.2). Steroid hormones such as 17β-oestradiol (E2)
and progesterone (P4) stimulate ABCG2 expression (Ee et al 2004a, Imai et al 2005,
Yasuda et al 2006, Wang et al 2008b), although several studies have shown that
sulphated conjugates of hormones (e.g. DHEA, 17β-oestradiol-17D-glucuronide) are
substrates exported by ABCG2 (Imai et al 2003, Suzuki et al 2003). E2 increased
ABCG2 mRNA and protein levels in the ER+ve BeWo human placental
choriocarcinoma and T-47D breast cancer cell lines (Ee et al 2004a, Yasuda et al 2006),
and a putative ERE has been characterised in the ABCG2 promoter which may account
for E2-induced increases in ABCG2 expression (Ee et al 2004b). However,
downregulation of ABCG2 mRNA and protein expression following E2 treatment has
also been described in BeWo cells, potentially resulting from use of different isolates or
passage number of cells between studies (Ee et al 2004a, Imai et al 2005, Wang et al
2006a). In MCF-7 cells, which express ERα, E2 did not alter ABCG2 mRNA but
decreased ABCG2 protein levels (Imai et al 2005). The decrease in ABCG2 levels was
associated with enhanced sensitivity of the cells to SN-38, an inhibitor of topoisomerase
I, and increased intracellular accumulation of topotecan in parental and in ABCG2-
overexpressing MCF-7 cells. These effects were shown to be mediated by ERα as the
ER-antagonist, tamoxifen reversed E2-mediated downregulation of ABCG2 protein
levels (Imai et al 2005). In contrast to BeWo cells, this study indicated that in MCF-7
cells, E2 did not alter ABCG2 transcription but induced post-translational modifications
of ABCG2 that decreased stability and maturation of the protein.
Progesterone (P4) also stimulates ABCG2 mRNA and protein expression (Wang et al
2006a, Yasuda et al 2009). In particular, P4 increased ABCG2 mRNA expression and
stimulated ABCG2 promoter activity in progesterone receptor isoform B (PRB)-
transfected but not in PRA-transfected BeWo cells, indicating that P4 effects on ABCG2
expression are mediated via PRB (Wang et al 2008b). In addition, PRB-stimulated
ABCG2 promoter activity was abrogated by PRA, supporting the previously reported
ability of PRA to suppress PRB activity (Wang et al 2008b). The Hedgehog/GLI
signalling pathway has been demonstrated in several cell types including human
embryonic kidney epithelial cells (293T), B-cell lymphoma (BJAB, SUDHL2) and
primary mediastinal B-cell lymphoma (PMBL) (U2940) cells, to upregulate ABCG2
expression, which involves binding of GLI1 to a single GLI binding site characterised
in the ABCG2 5’ promoter (Singh et al 2011). Elevated levels of ABCG2 mRNA and
Chapter 4
86
protein following treatment of 293T cells with the recombinant SHH N-terminal peptide
was abrogated by the Hedgehog inhibitor, cyclopamine-KAAD, supporting stimulation
of ABCG2 expression by the Hedgehog signalling pathway (Singh et al 2011).
ABCG2 expression may be regulated via post-translational modification of the
transporters which alters their maturity, stability and function. For example, the pro-
inflammatory cytokines, interleukin 6 (IL-6) and TNF-α did not have significant effects
on ABCG2 mRNA levels but increased ABCG2 protein expression, which was
hypothesised to be due to post-translational modification of the proteins (Mosaffa et al
2009). Pim-1L, a serine/threonine kinase, has been shown to induce phosphorylation of
ABCG2 at threonine 362, which was proposed to alter the conformation and subsequent
dimerisation or oligomerisation of ABCG2, with knockdown of Pim-1L expression in
drug-resistant prostate cancer cells abolishing ABCG2 multimer formation (Xie et al
2008). In support of these results, mutation of ABCG2 at threonine 362 (T362A)
inhibited ABCG2 trafficking to the plasma membrane and its drug export activity,
indicating the importance of threonine 362 for ABCG2 function (Xie et al 2008).
ABCG2 expression and function may be repressed by regulators which induce rapid
degradation of ABCG2 via the lysosomal or proteasomal degradation pathway
(Nakagawa et al 2009, Peng et al 2010). Compounds such as xanthines (e.g. caffeine,
theophylline, dyphilline) decreased ABCG2 protein levels by inducing ABCG2
degradation via the lysosome, and co-treatment of xanthine-treated MCF-7 cells
overexpressing ABCG2 (MCF-7/MX100) with the lysosome inhibitor, ammonium
chloride (NH4Cl) were able to restore ABCG2 protein levels (Ding et al 2012). In
association with these findings, xanthines increased the intracellular accumulation of
mitoxantrone and re-sensitised MCF-7/MX100 cells to mitoxantrone cytotoxicity (Ding
et al 2012). A novel ABCG2 inhibitor, PZ-39 stimulated endocytosis and lysosomal
degradation of ABCG2, with PZ-39 shown to bind directly to the ABCG2 protein (Peng
et al 2010). These studies provide evidence for a number of ABCG2 regulators that alter
ABCG2 expression and function by inducing degradation of the transporters via
common degradation pathways such as the lysosomal pathway.
Tyrosine kinase inhibitors (TKIs) such as lapatinib (Tykerb) and apatinib (YN968D1)
modulate ABCG2 function by binding to ATP-binding sites of ABCG2, potentially
Chapter 4
87
downregulating ATP-dependent functions of ABCG2 which include transport of
substrates. Photoaffinity labelling of ABCB1 and ABCG2 with [125I]
iodoarylazidoprazosin (IAAP) was inhibited by apatinib, suggesting that apatinib
interacts or binds to the ABC transporters, with apatinib binding at higher affinity to
ABCG2 substrate binding sites compared to ABCB1 substrate binding sites (Dai et al
2008, Mi et al 2010). Lapatinib and apatinib did not markedly alter ABCG2 mRNA and
protein expression but reversed the resistance of MCF-7 cells overexpressing ABCB1
and ABCG2 (e.g. MCF-7/ADR and MCF-7/FLV1000) to the cytotoxic effects of
doxorubicin and mitoxantrone, indicating that the TKIs inhibited ABC transporter
function without affecting ABC transporter expression (Dai et al 2008, Mi et al 2010).
Inhibition of ABC transporter localisation to the membrane surface, where the ABC
transporters function as drug efflux transporters, has been associated with increased
sensitivity of cells to drugs that are substrates of those transporters (Mizuarai et al 2004,
Robey et al 2007, Nakanishi 2012, To and Tomlinson 2013, Kathawala et al 2015). An
alternate mechanism of ABCG2-mediated drug resistance may involve ABCG2
localisation in membrane of extracellular vesicles (EV) located between neighbouring
cells that have been identified in mitoxantrone-resistant MCF-7 cells (MCF-7/MX)
(Ifergan et al 2005, Goler-Baron and Assaraf 2011). In that study, it was shown that
accumulation of ABCG2 substrates including mitoxantrone and topotecan into EV
structures sequestered these drugs from reaching intracellular targets, resulting in
resistance (Goler-Baron and Assaraf 2011). The formation of these vesicles may involve
PI3K/AKT signalling and treatment of MCF-7/MX cells with the PI3K/AKT pathway
inhibitor, LY294002 decreased the size and number of ABCG2-localising EV structures
and induced retention of ABCG2 and the ABCG2 substrate, riboflavin in the cell
cytoplasm (Goler-Baron et al 2012). LY294002 stimulated the sensitivity of cells to
topotecan, with the IC50 for topotecan decreased following treatment (Goler-Baron et al
2012), indicating that changes in ABCG2 cellular localisation impact the drug efflux
activity of the transporters.
The non-aromatisable androgen, DHT, and the Hedgehog pathway inhibitor,
cyclopamine have been shown previously to inhibit the growth of the ER+ve and PR+ve
breast cancer cell lines, MCF-7 and T-47D (Greeve et al 2004, Kubo et al 2004). Initial
studies in this thesis confirmed these findings and demonstrated using RT2 Profiler
Chapter 4
88
Human Breast Cancer Arrays that treatment of MCF-7 and T-47D cells with DHT,
cyclopamine, or DHT and cyclopamine downregulated the expression of breast cancer-
associated genes, including the mRNAs encoding the ABC transporters, ABCB1 and
ABCG2. This study has investigated DHT and cyclopamine induced regulation of
ABCG2 mRNA and protein expression, as well as ABCG2 function which was
evaluated by measuring the efflux rate of ABCG2 substrates from cells and sensitivity
of cells to cytotoxic ABCG2 substrates due to intracellular accumulation of the
substrates.
Chapter 4
89
4.2 Results
4.2.1 DHT and Cyclopamine Regulation of Gene Expression in Breast Cancer Cells
Prior to commencement of this PhD project (as part of my Honours project), effects of
the androgen, 5α-dihydrotestosterone (DHT) and the Hedgehog pathway inhibitor,
cyclopamine on gene expression were investigated in the MCF-7 and T-47D breast
cancer cell lines, which express functional AR and Hedgehog pathways (Horwitz et al
1975, Liberato et al 1993, Mukherjee et al 2006, Chua 2011, Aka and Lin 2012). DHT
and cyclopamine have independently been reported to inhibit the proliferation of breast
cancer cells including MCF-7 and T-47D cells (Greeve et al 2004, Kubo et al 2004) and
similarly, decreased proliferation of MCF-7 and T-47D cells was observed following 8
days of treatment with 10-8 M DHT or 2 µM cyclopamine, or co-treatment with 10-8 M
DHT and 2 µM cyclopamine (Figure 4.1A) (Chua 2011). These concentrations of DHT
and cyclopamine were shown previously to inhibit proliferation of breast cancer cells
but not to result in cell death (Chua 2011).
DHT and cyclopamine regulation of gene expression in MCF-7 and T-47D cells was
investigated using RT2 Profiler Human Breast Cancer PCR Arrays (SABiosciences),
which screens expression of 84 breast cancer-associated genes. Analysis of results of
the arrays using the SABiosciences web-based programme revealed that treatment of
MCF-7 and T-47D cells with the combination of 10-8 M DHT and 2 µM cyclopamine
for 24 h predominantly downregulated gene expression, with 28 genes downregulated
by ≥1.5-fold in both MCF-7 and T-47D cells. Genes which were downregulated
following DHT and cyclopamine treatments encoded inducers of cell proliferation,
including promoters of cell cycle progression, cyclin D1 (CCND1), cyclin D2 (CCND2)
and the MYC proto-oncogene, as well as anti-apoptosis factors, AKT1, APC, BCL2-
associated death promoter 2 (BAD), JUN and RASSF1 (Figure 4.1B).
Other genes found to be downregulated by DHT and cyclopamine co-treatment of the
cells were regulators of EMT (Section 1.7, Figure 4.1B), with DHT and cyclopamine-
induced downregulation of TGFB1, SRC and TWIST1 indicating reversal of EMT,
which can occur during mesenchymal-to-epithelial transition (MET) (Figure 4.1B).
Markers of the luminal breast cancer subtype, FOXA1, GATA3 and ESR1 were also
downregulated by co-treatment of MCF-7 and T-47D cells with DHT and cyclopamine
(Figure 4.1B). These markers are often used clinically in untreated cancers to predict
Chapter 4
90
responses of breast tumours to endocrine therapies such as the anti-oestrogen, tamoxifen
(Section 1.5). The implications of their downregulated expression in breast cancer cells
treated with DHT and cyclopamine are unknown at this time however androgen-induced
antagonism of the oestrogen responsiveness of breast cancer cells has been reported
previously (Peters et al 2009, Need et al 2012). Of interest, mRNA levels of the drug
efflux transporters, ABCB1 and ABCG2 were also markedly downregulated in both
MCF-7 and T-47D cells treated with the combination of DHT and cyclopamine (Figure
4.1B).
DHT and cyclopamine regulation of the ABC transporters, ABCB1 and ABCG2, was
investigated in this thesis study. As shown in Table 4.1, the threshold cycles (Ct value)
for ABCB1 exceeded 30 cycles (33.86 cycles in MCF-7 and 34.36 cycles in T-47D
cells) and for ABCG2, the Ct value was above 30 cycles in T-47D cells (33.54 cycles),
however in MCF-7 cells, the Ct value for ABCG2 was 27.73. Following analysis of the
genes using the web-based programme provided by manufacturer of the arrays (Section
3.8.8), the fold regulation of ABCB1 in MCF-7 cells was reported as “B” because the Ct
values for ABCB1 in both control and experimental samples exceeded 30 cycles,
thereby indicating low ABCB1 expression in MCF-7 cells. In addition, fold regulation
for both ABCB1 and ABCG2 was also reported as “B” in T-47D cells as Ct values were
>30 cycles (33 – 40 cycles), suggesting that ABCB1 and ABCG2 were expressed at very
low levels in T-47D cells, although ABCB1 and ABCG2 mRNA levels were
dowregulated following DHT and cyclopamine treatments (Table 4.1). As such, DHT
and cyclopamine regulation of ABCG2 expression and function were investigated using
MCF-7 cells.
4.2.2 DHT and Cyclopamine Regulation of ABCG2 mRNA Levels in MCF-7 Cells
Analysis of the RT2 Profiler Human Breast Cancer PCR Array data revealed that DHT
and cyclopamine individually reduced the mRNA levels of ABCG2 by 1.2 to 1.4 fold in
MCF-7 cells, while the combination of DHT and cyclopamine further reduced ABCG2
levels by 1.99 fold compared to the vehicle control (Table 4.1). To validate DHT and
cyclopamine induced downregulation of ABCG2 mRNA levels in MCF-7 cells using
RT-qPCR, RNA was extracted from MCF-7 cells (Section 3.8.1), reverse transcribed
(Section 3.8.2.1), with cDNA quality verified by GAPDH PCR (Section 3.8.5, 3.8.6; not
shown).
Chapter 4
91
(A)
(B) (i)
Anti-Apoptosis
Cell Cycle
EMT
DNA Damage
MC
F-7
(24h
rs)
AKT1 APC BAD CDKN1A JUN MUC1 SFN TP73 TWIST1 APC CCND2 CDKN1A JUN MYC RASSF1 SFN APC BRCA2 CDKN1A MAPK1 SFN TP73 ABCB1 ABCG2 SRC TGFB1 TWIST1 ESR1 FOXA1 GATA3 KRT8 ERBB2 GRB7 NOTCH1 ID1 SRC TGFB1 TWIST1
Xenobiotic Transporters
Breast Cancer Classification Markers
Control (0.1% (v/v) ethanol (vehicle)) 10-8 M DHT
2 μM Cyclopamine
10-8 M DHT + 2 μM Cyclopamine
0
5
10
15
Cel
l Num
ber
(×10
4 )
Treatment (8 days)
MCF-7
0
10
20
30
40
50
Cel
l Num
ber
(×10
4 )
Treatment (8 days)
T-47D
Chapter 4
92
(ii)
Figure 4.1: DHT and cyclopamine effects on cell proliferation and expression of breast cancer-associated genes. (A) Proliferation of MCF-7 and T-47D cells was estimated by MTS assays after 8 days of treatment with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT and 2 µM cyclopamine. Control cultures contained 0.1% (v/v) ethanol (vehicle). Results = mean ± S.E.M. (B) Heatmap of DHT and cyclopamine regulated genes in (i) MCF-7 and (ii) T-47D cells determined using RT2 Profiler Human Breast Cancer PCR Arrays. Green signals indicate downregulation, while red signals indicate upregulation of gene expression. DHT and cyclopamine treatments up- or downregulated by ≥1.5-fold a number of genes including anti-apoptosis factors, cell cycle regulators, the ABCB1 and ABCG2 (xenobiotic) transporters, regulators of epithelial-to-mesenchymal transition (EMT) and breast cancer classification markers.
Magnitude of log2 (Fold Change)
0 -2.432 2.432
Xenobiotic Transporters
T-47
D (2
4hrs
)
Anti-Apoptosis
Cell Cycle
EMT
Breast Cancer Classification Markers
ABCG2 ABCB1
BCL2 MYC AKT1 BAD APC JUN RASSF1 CCND1 SFN JUN RASSF1 PTEN TP53 BCL2 MYC
XBP1
SNAI2 TGFB1 TWIST1 NOTCH1 SRC TFF3 FOXA1 KRT18 SLC39A6
KRT8 ESR1 GATA3
ATM1 BRCA1 BRCA2 MGMT SFN TP53 TP73
DNA Damage
Chapter 4
93
Table 4.1: Regulation of ABCB1 and ABCG2 mRNA levels in MCF-7 and T-47D cells.
ABCB1 ABCG2
Average threshold cycle (Ct)
Fold up/down regulation
(status)
Average threshold cycle (Ct)
Fold up/down regulation
(status)
MCF-7
Vehicle control (0.1% (v/v) Ethanol)
33.86 - 27.73 -
10-8 M DHT 35.13 -2.45 (B) 28.06 -1.40 (OKAY)
2 µM Cyclopamine 33.57 1.19 (B) 27.97 -1.21 (OKAY)
10-8 M DHT + 2 µM Cyclopamine
37.44 -1.49 (B) 29.28 -1.99 (OKAY)
T-47D
Vehicle control (0.1% (v/v) Ethanol)
34.36 - 33.54 -
10-8 M DHT 35.81 -1.01 (B) 34.97 -1.75 (B)
2 µM Cyclopamine 40 -1.45 (B) 34.66 -2.02 (B)
10-8 M DHT + 2 µM Cyclopamine
37.11 -1.77 (B) 40 -3.12 (B)
Threshold cycles (Ct) and fold up- or downregulation of ABCB1 and ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 and T-47D cells compared to vehicle controls (0.1% (v/v) ethanol). A status (OKAY, A, B or C) was assigned to the fold regulation according to Ct values. ‘OKAY’ indicates that Ct values do not exceed 30 cycles; ‘A’ indicates that the average Ct is relatively high (>30 cycles) in either the control or experimental sample and Ct is low (<30 cycles) in the other sample; ‘B’ indicates low gene expression with Ct values exceeding 30 cycles in both control and experimental samples; ‘C’ indicates that gene expression may be very low or undetectable with Ct values in both control and experimental samples above the defined cut-off value of 35 cycles.
Chapter 4
94
To amplify ABCG2 cDNA (~187 bp), qPCR conditions including annealing temperature
and MgCl2 concentration were initially optimised, with gradient PCRs indicating
optimum annealing temperatures between 59ºC to 63.3ºC and an annealing temperature
of 60ºC used in subsequent studies (Figure 4.2A). To optimise MgCl2 concentration for
ABCG2 qPCR, efficiency curves were constructed from reactions containing cDNA
(2ng) diluted 10-fold to 1:1000 and increasing concentrations of MgCl2 (2-3.5 mM)
(Section 3.8.7). Melt curves with sharp peaks were observed for reactions containing all
MgCl2 concentrations, indicating appropriate amplification specificity, however ABCG2
qPCR amplification efficiencies were highest in reactions containing 3.5 mM MgCl2
(98.4%), which was used in subsequent studies (Figure 4.2B). qPCR conditions for the
housekeeping gene, β-actin had been optimised previously in the laboratory (data not
shown) (Section 3.8.7). Efficiency curves constructed for β-actin indicated that β-actin
qPCR efficiency was 97.0% (data not shown). Efficiency values for both ABCG2 and β-
actin qPCRs were within the accepted range for calculation of ABCG2 mRNA levels
using the Pfaffl method (Section 3.8.7).
Quantitation of ABCG2 mRNA levels following 24 h treatments of MCF-7 cells with
10-8 M DHT, 2 µM cyclopamine or a combination of 10-8 M DHT and 2 µM
cyclopamine indicated that in comparison to the vehicle control (0.1% (v/v) ethanol),
DHT treatment reduced ABCG2 mRNA levels by 34.8±0.044% while in cyclopamine-
treated MCF-7 cells, ABCG2 mRNA levels did not change (Figure 4.3). Following DHT
and cyclopamine co-treatment, ABCG2 mRNA levels were reduced by 30.8±0.041%
compared to the vehicle control, a similar reduction to that detected in MCF-7 cells
treated with DHT alone. Therefore, these experiments broadly confirmed results of the
PCR arrays, with DHT and DHT/cyclopamine treatments decreasing ABCG2 mRNA
levels and cyclopamine treatment inducing minimal effects on ABCG2 mRNA
expression.
4.2.3 DHT and Cyclopamine Regulation of ABCG2 Protein Levels in MCF-7 Cells
DHT and cyclopamine effects on ABCG2 protein levels were evaluated by western
blotting (Section 3.7). Prior to the commencement of these studies, ABCG2 primary
antibody concentrations were optimised by western blotting of whole cell lysates
derived from MCF-7 and T-47D cells using 1:1000, 1:750 and 1:500 dilutions of the
ABCG2 antibody (BXP-21 clone) (Figure 4.4A). The molecular weight of ABCG2 is
Chapter 4
95
reported to be 70-72 kDa based on analysis of the protein by SDS-PAGE under
denaturing conditions (Xu et al 2004, Diop and Hrycyna 2005). Similar to findings
from these reports, a prominent band at ~70 kDa was observed in MCF-7 but not T-47D
cell lysates at all ABCG2 antibody concentrations (Figure 4.4A). This correlated with
findings from the breast cancer PCR arrays which showed low endogenous ABCG2
expression in T-47D cells, with qPCR Ct values of >30 cycles in contrast to Ct values of
27.73 cycles in MCF-7 cells (Table 4.1). Additional bands at ~65 kDa, ~46 kDa and ~7
kDa were also detected in the western blots (Figure 4.4A). ABCG2 undergoes post-
translational modification, principally N-glycosylation, which increases protein stability
(Nakagawa et al 2009). Detection of ABCG2-immunoreactive proteins of lower
molecular weights, particularly, at ~65 kDa, which is similar to previously published
ABCG2 western blots from HeLa cells treated with peptide-N-glycosidase F (PNGase
F) or tunicamycin, which cleave N-linked glycans from glycoproteins, may indicate
incompletely glycosylated ABCG2 or ABCG2 degradation products (Diop and Hrycyna
2005, Nakagawa et al 2009). From these initial studies, a 1:750 dilution of ABCG2 was
chosen for subsequent investigation of ABCG2 protein expression.
DHT and cyclopamine regulation of ABCG2 protein levels was evaluated in MCF-7
cells following treatment with 10-8 M DHT, 2µM cyclopamine or 10-8 M DHT and 2 µM
cyclopamine for 0-8 days. ABCG2 levels were quantitated by densitometry, normalised
to corresponding β-actin levels for each lysate and expressed as a ratio of ABCG2 levels
at day 0 (Figure 4.4B). During the 8 days of treatment, DHT progressively decreased
ABCG2 protein levels, which were ~95% of controls at 24 h, but reduced to ~20% of
controls by day 8. Although cyclopamine had little effects on ABCG2 protein levels
which fluctuated around 100% at all timepoints, the combination of DHT and
cyclopamine treatments led to a more rapid reduction in ABCG2 protein levels
compared to DHT-treated cells, with ABCG2 levels reduced to ~55% of controls after
24 h of DHT/cyclopamine treatments and reaching a similar nadir of ~27% during the 8
days of treatment (Figure 4.4B).
4.2.4 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated
MCF-7 Cells
Full ABCG2 transporters localise predominantly to the plasma membrane where they
are functionally active as efflux transporters (Nakanishi 2012). As such, reduced
Chapter 4
96
(A)
(B)
2 mM MgCl2
2.5 mM MgCl2
1. 65ºC 2. 64.5ºC 3. 63.3ºC 4. 61.4ºC 5. 59ºC 6. 57ºC 7. 55.7ºC 8. 55ºC 9. Negative control (no cDNA)
1 2 3 4 5 6 7 8 9 ABCG2
(~187 bp)
3 mM MgCl2
Chapter 4
97
MgCl2 Efficiency (%) 2 mM 84.2
2.5 mM 86.0 3 mM 85.9
3.5 mM 98.4
Figure 4.2: Optimisation of ABCG2 qPCR conditions. RNA extracted from MCF-7 cells was reverse transcribed into cDNA. (A) To optimise ABCG2 PCR conditions, ABCG2 PCRs were performed using annealing temperatures between 55-65ºC and 2 mM MgCl2, with products separated in 2% agarose gels. (B) ABCG2 was amplified by qPCR in reactions of 10-fold dilutions of 2 ng cDNA. Annealing temperature was 60ºC and reactions with increasing concentrations of MgCl2 (2-3.5 mM) were prepared to optimise MgCl2 concentration for ABCG2 qPCR. Efficiency curves were generated for each of the PCRs and qPCR amplification efficiencies were calculated from these efficiency curves for each MgCl2 concentration.
3.5 mM MgCl2
Chapter 4
98
Figure 4.3: ABCG2 mRNA levels in DHT and cyclopamine treated MCF-7 cells. ABCG2 mRNA levels were quantitated by RT-qPCR in RNA isolated from MCF-7 cells following 24 h of treatment with 10-8 M DHT, 2 μM cyclopamine, 10-8 M DHT and 2 µM cyclopamine, or 0.1% (v/v) ethanol (vehicle control). Expression of ABCG2 was normalised to corresponding levels of β-actin. Duplicate samples were prepared in each experiment and results are expressed as mean ± S.E.M. of normalised ABCG2 mRNA levels from at least 3 independent experiments. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.
0
0.2
0.4
0.6
0.8
1
1.2
Control 10-8M DHT 2µMCyclopamine
10-8M DHT +2µM
Cyclopamine
Nor
mal
ised
AB
CG
2 m
RN
A L
evel
s
Treatment (24hrs)
* *
10-8 M DHT + 2 µM
Cyclopamine
2 µM Cyclopamine
10-8 M DHT Control
Chapter 4
99
(A)
(B) (i)
Day
10-8 M DHT
0 1 2 4 6 8
00.20.40.60.8
11.2
0 1 2 4 6 8Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Days
ABCG2 (70 kDa)
β-actin (44 kDa)
~70 kDa ~46 kDa
~7 kDa
1:500 ABCG2
1:750 ABCG2
1:1000 ABCG2
~40 kDa
Chapter 4
100
(ii)
(iii)
Figure 4.4: DHT and cyclopamine regulation of ABCG2 protein levels. (A) ABCG2 immunoblotting was optimised using whole cell lysates from MCF-7 and T-47D cells and increasing concentrations of ABCG2 antibodies. (B) ABCG2 protein levels in MCF-7 cells following 8 days of treatment with (i) 10-8 M DHT, (ii) 2 µM cyclopamine or (iii) 10-8 M DHT and 2 µM cyclopamine were determined by immunoblotting, with levels normalised against β-actin blots for each sample. Experiments were repeated three times and representative blots are shown.
0 1 2 4 6 8
2 μM Cyclopamine
Day
00.20.40.60.8
11.21.4
0 1 2 4 6 8Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Days
ABCG2 (70 kDa)
β-actin (44 kDa)
0 1 2 4 6 8
10-8 M DHT + 2 μM Cyclopamine
Day
00.20.40.60.8
11.2
0 1 2 4 6 8
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Days
ABCG2 (70 kDa)
β-actin (44 kDa)
Chapter 4
101
ABCG2 localisation at the plasma membrane indicates comparatively decreased
ABCG2 efflux activity. To investigate DHT and cyclopamine effects on the intracellular
localisation of ABCG2, immunofluorescence microscopy was used to localise ABCG2
in situ. For these studies, primary and secondary antibodies for detection of ABCG2
were optimised using immunofluorescence microscopy, with (background) signals from
cells stained with Alexafluor® 488-conjugated anti-mouse secondary antibodies (no
primary antibody) dull in contrast to the higher non-specific signals from the
Alexafluor® 546-conjugated anti-mouse secondary antibodies (Figure 4.5A). Therefore,
secondary antibodies conjugated with Alexafluor® 488 were used for detection of
ABCG2 intracellular localisation.
To determine the optimum concentration of the ABCG2 primary antibody (BXP-21
clone) for immunofluorescence microscopy, MCF-7 cells were immunostained with
either 1:750 or 1:500 dilutions of the ABCG2 antibody and Alexafluor® 488-conjugated
anti-mouse secondary antibodies (Section 3.3). At the 1:750 dilution of ABCG2
antibody, staining was weak and the localisation of ABCG2 was unclear in these cells
(Figure 4.5B). In contrast, at a 1:500 dilution of the ABCG2 antibody, diffuse ABCG2
immunoreactivity was observed in the nucleus and cytoplasm of cells, with strong
ABCG2 signals accumulating in cell-to-cell membrane junctions (yellow arrows) as
well as in round vesicles (red arrows) in the cytoplasm of cells (Figure 4.5B). A 1:500
dilution of ABCG2 antibody was used for subsequent immunofluorescence microscopy
studies. To further investigate ABCG2 localisation in MCF-7 cells and to verify its
apparent nuclear and cytoplasmic localisation, subcellular fractionation was performed
(Section 3.6). For these studies, proteins were isolated from nuclear and cytoplasmic
fractions of MCF-7 cells as well as the residual cell pellet, which would contain proteins
from the cell membrane, and ABCG2 protein levels were evaluated by western blotting
(Section 3.6, 3.7). ABCG2 protein bands at ~70 kDa were detected in nuclear and
membrane fractions of MCF-7 cells (Figure 4.6). In contrast, ~70 kDa ABCG2-
immunoreactive bands were not observed in cytoplasmic fractions, although diffuse
cytoplasmic ABCG2 staining had been detected by immunofluorescence microscopy
(Figure 4.5, 4.7). Detection of ABCG2 signals at lower molecular weights in all
fractions may indicate protein cleavage or degradation occurring during processing for
these studies or as a normal part of the intracellular turnover of ABCG2. The clear
selectivity of histone H3 and α-tubulin in nuclear and cytoplasmic fractions,
respectively, indicated lack of cross-contamination of these proteins, while detection of
Chapter 4
102
histone H3 in membrane fractions suggested that not all nuclei were ruptured under
these conditions (Figure 4.6). However overall, results of these experiments supported
initial findings from analysis of the intracellular localisation of ABCG2 using
immunofluorescence microscopy. Further studies will be required to determine whether
the ABCG2-containing cytoplasmic vesicles would be ruptured in the buffers used, or
whether they would remain intact and their contents collected in the final membrane
fractions.
As the downregulation of ABCG2 protein levels induced by DHT and the combination
of DHT and cyclopamine treatments of MCF-7 cells was evident at day 4 of the
treatments, DHT and cyclopamine regulation of the intracellular localisation of ABCG2
was assessed following treatment of MCF-7 cells with 10-8 M DHT and/or 2 µM
cyclopamine for 0-4 days (Section 3.3). In control MCF-7 cultures treated with vehicle
(0.1% (v/v) ethanol) alone, strong accumulation of ABCG2 signals in cell-to-cell
junction complexes (yellow arrows) and in round cytoplasmic vesicles (red arrows) was
evident, with the marker of filamentous actin (F-actin), Phalloidin Red shown to co-
localise with the ABCG2+ve cell-to-cell junction complexes as well as ABCG2-
containing cytoplasmic vesicles, in particular around the edges of these vesicles (Figure
4.7). In MCF-7 cultures treated with 10-8M DHT, ABCG2 staining in cell-to-cell
junction complexes as well as in cytoplasmic vesicles was diminished and these results
were similarly observed in DHT/cyclopamine co-treated cells, suggesting that DHT and
the combination of DHT and cyclopamine reduced ABCG2 function at the membrane
(Figure 4.7). In MCF-7 cells treated with 2µM cyclopamine, ABCG2-associated cell-to-
cell junction complexes decreased but interestingly, cyclopamine induced ABCG2
accumulation in cytoplasmic vesicles, indicating that cyclopamine may also be reducing
ABCG2 efflux function but via a distinct mechanism (Figure 4.7).
4.2.5 DHT and Cyclopamine Effects on ABCG2 Protein Degradation
Degradation or turnover of proteins is critical for clearing of mis-folded or damaged
proteins as well as for controlling the cellular content of proteins. The two most
common protein degradation pathways in humans are the ubiquitin/proteasome system
and the lysosomal pathway. The large cytoplasmic ABCG2-containing vesicles in
MCF-7 cells that co-localised with F-actin closely resembled aggresomes (Wakabayashi
et al 2007) (Figure 4.7). Following events such as non-rapid clearing of proteins or
Chapter 4
103
(A)
(B)
Hoechst 33258 (blue) Merge Alexafluor® 488 (green)
Alexafluor® 546 (red) Hoechst 33258 (blue) Merge
ABCG2 (green)
Hoechst 33258 (blue)
ABCG2 + Hoechst 33258
1:750 ABCG2 1:500 ABCG2
Chapter 4
104
Figure 4.5: Optimisation of primary and secondary antibody concentrations for investigation of ABCG2 intracellular localisation by immunofluorescence microscopy. (A) MCF-7 cells cultured on coverslips were immunostained with 1:400 Alexafluor® 488 (green) or 1:400 Alexafluor® 546 (red) labelled anti-mouse secondary antibodies. (B) ABCG2 primary antibody was tested at concentrations of 1:750 or 1:500, which was detected using 1:400 Alexafluor® 488 (green) labelled anti-mouse secondary antibodies. Cell nuclei were stained with Hoechst 33258 (blue) and immunostaining was evaluated using a Nikon Eclipse Ti-e fluorescence microscope. Scale bar: 30 µm. Yellow and red arrows indicate ABCG2 signals in cell-to-cell junction complexes and in round cytoplasmic vesicles, respectively.
Chapter 4
105
Figure 4.6: Intracellular localisation of ABCG2 in MCF-7 cells. Proteins isolated from the cell membrane, cytoplasm and nuclear fractions of MCF-7 cell lysates were immunoblotted for ABCG2. α-tubulin and histone H3 western blots were used as loading controls for cytoplasmic and nuclear proteins, respectively. Representative blots are shown.
Lanes 1 and 2: MCF-7 (nuclear fraction) Lanes 3 and 4: MCF-7 (cytoplasmic fraction) Lanes 5 and 6: MCF-7 (membrane fraction) Lane 7: MCF-7 whole cell lysate
Histone H3 (15 kDa)
ABCG2 (~70kDa)
α-tubulin (52 kDa)
~46 kDa ~58 kDa
~35 kDa
1 2 3 4 5 6 7
Chapter 4
106
10-8 M DHT
2 µM Cyclopamine
10-8 M DHT + 2 µM
Cyclopamine
ABCG2 (green) F-actin (red) ABCG2 + F-actin +
Hoechst 33258
Vehicle Control
(0.1% (v/v) ethanol)
Negative Control
(no 1º Ab)
ABCG2 (green) Hoechst 33258 (blue) ABCG2 + Hoechst 33258
Chapter 4
107
Figure 4.7: Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in MCF-7 cells. MCF-7 cells grown on coverslips were treated with 10-8 M DHT, 2 μM cyclopamine or 10-8 M DHT + 2 μM cyclopamine for 4 days, then immunostained with ABCG2 primary and Alexafluor® 488-conjugated anti-mouse secondary antibodies. Filamentous actin (F-actin, red) and nuclei (blue) were stained with Phalloidin Red and Hoechst 33258, respectively. Negative controls were stained with secondary antibodies alone. ABCG2 accumulated in cell-to-cell junction complexes (yellow arrow) and in round cytoplasmic vesicles (red arrow) in MCF-7 cells. Experiments were repeated three times and representative results are shown. Scale bar: 30 µm.
Chapter 4
108
inhibition of degradation pathways including the proteasome, proteins that are tagged
for degradation can accumulate into aggregates or aggresomes (Garcia-Mata et al 2002,
Zaarur et al 2014). As such, it was feasible that the large cytoplasmic ABCG2-
containing vesicles may be associated with degradation of ABCG2 proteins. In initial
studies, proteasomal degradation of ABCG2 was investigated using the proteasome
inhibitor, MG132.
To optimise MG132 treatment of MCF-7 cells, cultures were treated with increasing
concentrations of 1-3 µM MG132 for 6, 8 or 24 h prior to collection of cell lysates for
ABCG2 immunoblotting (Figure 4.8). These concentrations of MG132 did not induce
marked cell death in cultures at all timepoints tested. After 6 and 8 h of MG132
treatment, normalised ABCG2 levels were similar to those in untreated controls (1.1 to
1.4 fold) and similarly at 24 h, ABCG2 levels were 0.9 to 1.1 fold of those in control
cultures (Figure 4.8). These data indicated that the proteasome may not be involved in
the degradation of endogenous ABCG2 protein, and are in agreement with previous
reports indicating that only mutant or mis-folded ABCG2 proteins lacking disulphide
bonds are preferentially degraded by the proteasome (Wakabayashi et al 2007). To
investigate involvement of the proteasome in the regulation of ABCG2 levels in DHT
and cyclopamine treated MCF-7 cells, cultures were pre-treated with 10-8 M DHT
and/or 2 µM cyclopamine for 2 days, which reduced ABCG2 protein levels (Figure 4.4)
prior to addition of 2 µM MG132 to the cultures for 6 h. In support of results obtained
during optimisation of MG132 treatment of cells (Figure 4.8), ABCG2 protein levels
were not altered in vehicle control cultures (0.1% (v/v) ethanol) following addition of
MG132 (Figure 4.9). Similarly, in cyclopamine-treated MCF-7 cells, in which ABCG2
protein expression was ~1.28 fold that in controls, MG132 treatment decreased these
levels by ~20%. In comparison to controls, DHT and the combination of DHT and
cyclopamine reduced ABCG2 protein levels by ~15% and ~40%, respectively, and
treatment of these cells with MG132 further decreased ABCG2 levels in DHT-treated
cells by ~10% but increased ABCG2 protein levels by 36% in cells co-treated with
DHT and cyclopamine (Figure 4.9). These results showed only modest effects of
proteasomal inhibition of ABCG2 protein levels and in addition were difficult to
reproduce in replicate experiments.
Chapter 4
109
Degradation of proteins via the lysosomal pathway involves fusion of proteins or
protein-containing organelles such as the endosomes and autophagosomes by the
lysosomes, in which proteins are degraded by acid hydrolases (Dunn 1990, Alberts et al
2002). Several lines of evidence indicate that lysosomes are recruited to and degrade
proteins in aggresomes (Iwata et al 2005a, Iwata et al 2005b, Zaarur et al 2014). To
investigate whether ABCG2 degradation involves the lysosomal pathway, regulation of
ABCG2 protein expression by the lysosome inhibitor, chloroquine was assessed. To
optimise chloroquine concentration and duration of treatment, MCF-7 cells that had
been treated with the combination of 10-8 M DHT and 2 µM cyclopamine for 4 days
were cultured with 25 µM, 50 µM or 100 µM chloroquine for 6, 24 and 48 h prior to
lysis of the cells for immunoblotting. Minimal cell toxicity or cell death was observed in
cultures treated with the lowest concentration of chloroquine (25 µM), which led to a
gradual increase in ABCG2 protein levels that were initially downregulated by ~80%
(compared to vehicle controls) following 4 days of DHT and cyclopamine co-treatment
of MCF-7 cells (Figure 4.10A). After addition of chloroquine to DHT and cyclopamine-
treated cultures for 48 h, ABCG2 protein was restored to levels that were similar to
vehicle/untreated controls. This result was in agreement with a previous study which
showed that ABCG2 is predominantly degraded by the lysosomal pathway
(Wakabayashi et al 2007). At the higher concentration of 50 µM chloroquine, ABCG2
protein levels were progressively decreased in cultures that had been pre-treated with
DHT and cyclopamine, with levels reduced to ~13% of vehicle controls at the 48 h
timepoint (Figure 4.10B). In cultures treated with highest concentration of chloroquine
(100 µM), changes in ABCG2 protein expression after 48 h of chloroquine treatment
were not able to be assessed as the extensive cell death and detachment of cells from the
culture surface resulted in low protein yields. At 6 and 24 h post addition of 100 µM
chloroquine to the cultures, ABCG2 levels were comparable to levels observed in cells
treated with DHT and cyclopamine alone (Figure 4.10B).
Chloroquine treatment of control (vehicle-treated) MCF-7 cells increased ABCG2
protein levels by up to 1.6-1.7-fold after 24 h but these levels declined following
treatment with 25 µM chloroquine for 48 h, potentially due to non-specific cytotoxicity
induced by lysosomal inhibition for this length of time (Figure 4.11A). In MCF-7
cultures pre-treated for 4 days with DHT and the combination of DHT and cyclopamine,
ABCG2 levels were decreased by 35% and 45%, respectively, a result similar to
previous findings (Figure 4.4, 4.11B, 4.11D). Addition of 25 µM chloroquine to DHT-
Chapter 4
110
treated cultures led to the progressive reduction of ABCG2 levels, with ABCG2 protein
levels decreased by 72% compared to vehicle controls after 48 h (Figure 4.11B). In
DHT and cyclopamine co-treated cells, ABCG2 protein levels were further reduced at 6
and 24 h post addition of chloroquine but by 48 h, up to ~2-fold increases in these levels
were observed (Figure 4.11D). Similar to DHT-treated cells, 25 µM chloroquine
treatment of cyclopamine-treated MCF-7 cells gradually decreased ABCG2 protein
levels during 48 h of co-culture (Figure 4.11C). Although these findings suggested
involvement of the lysosome in regulation of ABCG2 levels, results were again difficult
to reproduce, potentially due to toxicity of chloroquine in MCF-7 cells.
To further investigate these findings, intracellular localisation of the ABCG2-containing
cytoplasmic vesicles and the lysosomes, which were stained by Lysotracker Red, was
evaluated by immunofluorescence microscopy. Optimisation of the concentration and
duration of Lysotracker Red staining was carried out by incubating MCF-7 cells with 50
nm or 100 nm Lysotracker Red for 10, 20 or 30 minutes prior to fixation and
preparation of cells for immunofluorescence microscopy (Section 3.3). Punctate
staining of Lysotracker Red in the cell cytoplasm was evident after 10 and 20 minutes
of incubation of MCF-7 cells with 50 nM Lysotracker Red (Figure 4.12A). Similar
punctate staining was observed in cultures incubated with 100 nM Lysotracker Red for
10 minutes although the intensity of Lysotracker Red was stronger in these cultures
compared to those incubated with 50 nM Lysotracker Red (Figure 4.12A, 4.12B).
Prolonged incubation of the cells with Lysotracker Red resulted in formation of
Lysotracker Red-containing aggregates, which may indicate over-staining of the cells
(Figure 4.12A, 4.12B). For subsequent studies, cells were stained for 20 minutes with
50 nM Lysotracker Red.
To investigate whether the ABCG2-containing cytoplasmic vesicles co-localise with the
lysosomes, 50 nM Lysotracker Red was added for 20 minutes to MCF-7 cultures pre-
treated with 0.1% (v/v) ethanol (vehicle control) or 2 µM cyclopamine for 4 days which
was previously shown to induce accumulation of ABCG2 into cytoplasmic vesicles
(Figure 4.7). In both the vehicle control and cyclopamine-treated MCF-7 cells, co-
localisation of ABCG2 signals, especially in ABCG2-containing cytoplasmic vesicles,
and Lysotracker Red was not observed (Figure 4.12C), thereby indicating that ABCG2
in the vesicles did not fuse to lysosomes for lysosomal degradation.
Chapter 4
111
(A)
(B)
(C)
β-actin (44 kDa)
ABCG2 (70 kDa)
0 1 2 3 MG132 (µM)
6 h
00.20.40.60.8
11.2
0 1 2 3Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
[MG132] (µM)
β-actin (44 kDa)
ABCG2 (70 kDa) 0 1 2 3 MG132 (µM)
8 h
00.20.40.60.8
11.21.4
0 1 2 3Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
[MG132] (µM)
β-actin (44 kDa) ABCG2 (70 kDa)
0 1 2 3 MG132 (µM)
24 h
00.20.40.60.8
11.2
0 1 2 3Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
[MG132] (µM)
Chapter 4
112
Figure 4.8: Optimisation of experimental conditions for treatment of MCF-7 cells with the proteasome inhibitor, MG132. MCF-7 cells cultured in 6-well plates were treated with increasing concentrations of MG132 (1-3 µM) for (A) 6, (B) 8 or (C) 24 h and cell lysates were collected for western blotting. ABCG2 protein levels were normalised to corresponding β-actin levels and expressed as a ratio of ABCG2 levels in untreated MCF-7 cells (0 µM MG132). Experiments were repeated three times and representative blots are shown.
Chapter 4
113
(A)
(B)
(C)
00.20.40.60.8
11.2
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s Treatment
β-actin (44 kDa)
ABCG2 (70 kDa)
- + MG132 (2 µM)
Vehicle Control
Vehicle Control
β-actin (44 kDa)
ABCG2 (70 kDa)
- + MG132 (2 µM)
DHT (2 days)
00.20.40.60.8
11.2
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
β-actin (44 kDa)
ABCG2 (70 kDa)
- + MG132
Cyclopamine (2 days)
Vehicle Control
00.20.40.60.8
11.21.4
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
Chapter 4
114
(D)
Figure 4.9: MG132 effects on the regulation of ABCG2 protein in DHT and cyclopamine treated MCF-7 cells. MCF-7 cells cultured for 2 days with (A) 0.1% (v/v) ethanol (vehicle control), (B) 10-8 M DHT, (C) 2 µM cyclopamine or (D) 10-8 M DHT and 2 µM cyclopamine were treated for 6 h with 2 µM MG132 prior to protein isolation and ABCG2 immunoblotting. ABCG2 protein levels were normalised to β-actin levels and expressed as a proportion of normalised ABCG2 protein levels in controls. Experiments were repeated at least three times and representative results are shown.
β-actin (44 kDa)
ABCG2 (70 kDa)
- + MG132 (2 µM)
DHT + Cyclopamine
(2 days) Vehicle Control
00.20.40.60.8
11.2
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
Chapter 4
115
00.20.40.60.8
11.21.4
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
00.20.40.60.8
11.2
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
(A)
(B)
ABCG2 (70 kDa)
β-actin (44 kDa)
24h 48h Vehicle Control
DHT + Cyclopamine (4 days)
6h 0h
100 µM Chloroquine
ABCG2 (70 kDa)
β-actin (44 kDa)
DHT + Cyclopamine (4 days)
6h 24h 24h 48h Vehicle Control
50 µM Chloroquine
6h 0h
25 µM Chloroquine
Chapter 4
116
Figure 4.10: Treatment of MCF-7 cells with the lysosome inhibitor, chloroquine. MCF-7 cells were cultured with ethanol (0.1% (v/v), vehicle control) or a combination of 10-8
M DHT and 2 µM cyclopamine for 4 days. At 6, 24 and 48 h prior to harvesting of the cells, (A) 25 µM, (B) 50 µM or 100 µM chloroquine was added to the cultures. Due to chloroquine-induced cytotoxicity, cells were treated with 100 µM chloroquine for 6 and 24 h only. ABCG2 protein levels determined by immunoblotting were normalised against β-actin immunoblots for each lane and compared to ABCG2 protein levels in vehicle-treated controls. Experiments were repeated at least three times and representative blots are shown.
Chapter 4
117
00.20.40.60.8
11.21.4
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
0
0.2
0.4
0.6
0.8
1
1.2
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
(A)
(B)
(C)
β-actin (44 kDa)
ABCG2 (70 kDa)
- Chloroquine (25 µM)
Vehicle Control
24h 6h 48h
00.20.40.60.8
11.21.41.61.8
Nor
mal
ised
AB
CG
2 Pr
otei
n L
evel
s
Treatment
β-actin (44 kDa)
ABCG2 (70 kDa)
Vehicle Control - Chloroquine (25 µM)
Cyclopamine (4 days)
24h 6h 48h
β-actin (44 kDa) ABCG2 (70 kDa)
Vehicle Control - Chloroquine (25 µM)
DHT (4 days)
24h 6h
h
48h
Chapter 4
118
(D)
Figure 4.11: Effects of lysosomal inhibition on DHT and cyclopamine induced regulation of ABCG2 protein levels. MCF-7 cells were pre-treated for 4 days with (A) 0.1 (v/v) ethanol (vehicle control), (B) 10-8 M DHT, (C) 2 µM cyclopamine or (D) 10-8
M DHT + 2 µM cyclopamine prior to addition of 25 µM chloroquine for 6, 24 and 48 h and protein extraction for immunoblotting. ABCG2 protein levels were normalised to β-actin and expressed as a proportion of ABCG2 protein levels in vehicle treated controls. Experiments were repeated at least three times and representative results are shown.
0
0.2
0.4
0.6
0.8
1
1.2
Nor
mal
ised
AB
CG
2 Pr
otei
n Le
vels
Treatment
β-actin (44 kDa)
ABCG2 (70 kDa)
Vehicle Control - Chloroquine (25 µM)
DHT + Cyclopamine (4 days)
24h 6h 48h
Chapter 4
119
(A)
(B)
Lysotracker Red Hoechst 33258 (blue) Merge
10 min
20 min
30 min
Lysotracker Red Hoechst 33258 (blue) Merge
10 min
20 min
30 min
Chapter 4
120
(C)
Figure 4.12: Intracellular co-localisation of ABCG2 and lysosomes. To optimise use of the lysosomal marker, Lysotracker Red, MCF-7 cells cultured on glass coverslips were incubated with (A) 50 nM or (B) 100 nM Lysotracker Red for 10, 20 or 30 minutes. (C) MCF-7 cells pre-treated for 4 days with 0.1% (v/v) ethanol (vehicle control) or 2 µM cyclopamine were incubated with 50 nM Lysotracker Red for 20 minutes, then immunostained for ABCG2 (green). Cell nuclei (blue) were stained using Hoechst 33258. Coverslips were viewed by immunofluorescence microscopy. Scale bar: 30 µm.
Lysotracker Red ABCG2 (green) Lysotracker Red/
ABCG2/Hoechst 33258
Vehicle Control
2 µM Cyclopamine
(4 days)
Chapter 4
121
Interestingly, the punctate staining of Lysotracker Red was found to be in close
proximity around the ABCG2 cytoplasmic vesicles (Figure 4.12C). A similar
localisation of the lysosomes around aggresomes has been reported in previous studies
(Korolchuk et al 2011, Zaarur et al 2014) and was crucial for lysosomal-mediated
degradation of proteins in the aggresomes. Based on the findings reported previously
(Korolchuk et al 2011, Zaarur et al 2014), clustering of Lysotracker Red around the
ABCG2-containing cytoplasmic vesicles indicate that proteins in these vesicles
including ABCG2 may be degraded by the lysosomes.
4.2.6 DHT and Cyclopamine Regulation of ABCG2 Efflux Activity
The amino acid at position 482 in the third transmembrane domain (TMD3) of ABCG2
protein plays a critical role in ABCG2 efflux activity and specificity for export of
substrates including the fluorescent molceules, Rhodamine 123 and mitoxantrone
(Honjo et al 2001, Robey et al 2003, Ejendal et al 2006). A base substitution resulting
in changes from arginine of wild-type ABCG2, to glycine (Gly482) or threonine (Thr482)
in ABCG2 variants increases the specificity of ABCG2 for Rhodamine 123 and
mitoxantrone efflux, while ABCG2 with arginine at position 482 preferentially exports
mitoxantrone (Honjo et al 2001). That study identified that ABCG2 (Arg482) in parental
MCF-7 cells, but showed that MCF-7 cells selected for resistance to adriamycin and
verapamil (MCF-7/AdVp3000) expressed ABCG2 with Thr482 (Honjo et al 2001).
To determine ABCG2 sequence in the MCF-7 cells used for these studies, the ABCG2
coding sequence was analysed by Sanger sequencing (Section 3.9). Sequencing of the
PCR products indicated that arginine (Arg), encoded by “AGG” (positions 1792 to 1794
of the coding sequence) was present at position 482 of the ABCG2 amino acid sequence
(Figure 4.13B). According to findings published by Honjo and colleagues, these cells
would preferentially export mitoxantrone in comparison to Rhodamine 123 (Honjo et al
2001). This was confirmed by measurement of export of the ABCG2 substrates,
Rhodamine 123 and mitoxantrone from MCF-7 cells by flow cytometric analysis of
intracellular levels of the fluorescent substrates (Section 3.4).
In these experiments, forward scatter (FSC) and side scatter (SSC) plots were used for
gating the MCF-7 cell population (Figure 4.14), from which viable MCF-7 cells were
identified by exclusion of 7-aminoactinomycin D (7-AAD), a marker that binds to non-
Chapter 4
122
viable cells. Background fluorescence was estimated using negative controls consisting
of MCF-7 cells which had not been incubated with mitoxantrone or Rhodamine 123 and
was used to differentiate background signals in cell populations that had been incubated
with mitoxantrone or Rhodamine 123 (Figure 4.14). Fluorescence signals of the
ABCG2 substrates (Rhodamine 123 and mitoxantrone) in the viable cells were gated in
7-AAD vs mitoxantrone plots (Figure 4.14), results of which were used to construct
histograms quantitating of the mean fluorescence intensity (MFI) of mitoxantrone or
Rhodamine 123 (Figure 4.14).
To evaluate the export rate of Rhodamine 123 and mitoxantrone from MCF-7 cells,
cells were incubated with 0.5 µg/mL Rhodamine 123 or 0.5, 1 and 5 µM mitoxantrone
for 60 minutes to allow passive diffusion of the molecules into the cells. Cultures were
then incubated in substrate-free medium (efflux phase) for a further 1-24 h, during
which export of substrates was monitored by determining the remaining intracellular
fluorescence levels of the substrates (Section 3.4). After 2, 4 and 18 h, no marked
changes were observed for Rhodamine 123 mean fluorescent intensities (MFIs) in
comparison to Rhodamine 123 fluorescence at time 0 of the efflux phase, with
Rhodamine 123 MFI increased slightly by 2.7-3.3% after 2 and 4 h of efflux and
decreased by 1.6% after 18 h (Figure 4.15). Prolonged culture of the cells (24 h) led to
reduction of Rhodamine 123 fluorescent intensity by 27%, indicating that the efflux of
Rhodamine 123 from MCF-7 cells was weak, a result that is in line with previous
findings (Figure 4.15) (Honjo et al 2001). In contrast, export of mitoxantrone from
MCF-7 cells was more evident and the mean fluorescence intensity of mitoxantrone was
decreased by ~25% following 1 h of efflux in cells which were pre-incubated with 0.5
µM and 5 µM mitoxantrone. In cells incubated with 1 µM mitoxantrone, mitoxantrone
fluorescence levels were reduced by ~34% after 1 h of mitoxantrone efflux (Figure
4.16).
To investigate DHT and cyclopamine effects on ABCG2 efflux activity, MCF-7
cultures that had been pre-treated with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT
+ 2 µM cyclopamine for 8 days were incubated with 1 µM mitoxantrone for 60 minutes.
Cells were then cultured for 60 minutes in mitoxantrone-free medium, during which
intracellular mitoxantrone mean fluorescence intensity (MFI) was quantitated every 15
minutes by flow cytometry (Section 3.4). In vehicle control treated MCF-7 cells,
Chapter 4
123
(A)
(B)
61 AAAACTGTTATCTGATTTATTACCCATGAGGATGTTACCAAGTATTATATTTACCTGTAT 120
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
1764 AAAACTGTTATCTGATTTATTACCCATGAGGATGTTACCAAGTATTATATTTACCTGTAT 1823
Figure 4.13: ABCG2 exon 12 cDNA sequence in MCF-7 cells. (A) mRNA extracted from MCF-7 cells was reverse transcribed, ABCG2 exons 11 to 13 were PCR-amplified and PCR products were electrophoresed in a 2% agarose gel. (B) Purified ABCG2 PCR products were sequenced by Sanger sequencing, which identified that codon 482 in exon 12, AGG, would encode arginine.
Arginine
~150 bp
Chapter 4
124
(A) (i)
SSC
FSC
MCF-7
Mitoxantrone (MX) Fluorescence
7-AA
D F
luor
esce
nce
MX+ve/7-AAD-ve
MX-ve/7-AAD-ve
MX-ve/7-AAD+ve
(ii)
Mitoxantrone (MX) Fluorescence
7-AA
D F
luor
esce
nce
MX+ve/7-AAD-ve
(iii)
Cou
nt
Mitoxantrone (MX) Fluorescence
MX+ve/7-AAD-ve
(iv)
Chapter 4
125
Figure 4.14: Flow cytometric analysis of intracellular levels of the ABCG2 substrates, (A) mitoxantrone (MX) and (B) Rhodamine 123 (Rhd123) in MCF-7 cells. MCF-7 cells were incubated with 1µM mitoxantrone or 0.5 µg/mL Rhodamine 123 for 60 minutes prior to trypsinisation and staining with the cell viability marker, 7-AAD. (i) Forward (FSC) and side scatter (SSC) plots were used to identify the MCF-7 cell population. (ii) Background fluorescence was determined from MCF-7 cells that had not been incubated with mitoxantrone or Rhodamine 123 (iii) 7-AAD vs MX or 7-AAD vs Rhd123 plots were constructed to detect mitoxantrone (MX+ve/7-AAD-ve) or Rhodamine 123 (Rhd123+ve/7-AAD-ve) fluorescence signals in viable cells. (iv) MX or Rhd123 mean fluorescence intensity (MFI) was quantitated from corresponding fluorescence histograms.
SSC
FSC
MCF-7
(B) (i)
7-AA
D F
luor
esce
nce
Rhodamine123 Fluorescence
Rhd123+ve/7-AAD-ve
Rhd123-ve/7-AAD-ve
Rhd123-ve/7-AAD+ve
(ii) 7-
AAD
Flu
ores
cenc
e
Rhodamine 123 Fluorescence
Rhd123+ve/7-AAD-ve
(iii)
Rhodamine 123 Fluorescence
Cou
nt Rhd123+ve/7-AAD-ve
(iv)
Chapter 4
126
(A)
(B)
(C)
Cou
nt
Rhodamine 123 Fluorescence
Efflux (0h) Efflux (2h)
0
20
40
60
80
100
120
Efflux (0h) Efflux (2h)
Rho
dam
ine
123
Mea
n Fl
uore
scen
ce In
tens
ity
(%)
Cou
nt
Rhodamine 123 Fluorescence
Efflux (0h) Efflux (4h)
0
20
40
60
80
100
120
Efflux (0h) Efflux (4h)
Rho
dam
ine
123
Mea
n Fl
uore
scen
ce In
tens
ity
(%)
Cou
nt
Rhodamine 123 Fluorescence
0
20
40
60
80
100
120
Efflux (0h) Efflux (18h)
Rho
dam
ine
123
Mea
n Fl
uore
scen
ce In
tens
ity
(%)
Efflux (0h) Efflux (18h)
Chapter 4
127
(D) Figure 4.15: Efflux of Rhodamine 123 from MCF-7 cells. MCF-7 cells were incubated with 0.5 µg/mL Rhodamine 123 for 60 minutes and Rhodamine 123 mean fluorescence intensity (MFI) of cells was evaluated by flow cytometry at 0 h (Efflux (0h)) or following a further (A) 2, (B) 4, (C) 18 or (D) 24 h of culture in Rhodamine 123-free culture medium. Rhodamine 123 MFI (%) was expressed as a proportion of Rhodamine 123 fluorescence at 0 h of efflux. Experiments were repeated at least three times and representative results are shown.
Cou
nt
Rhodamine 123 Fluorescence
0
20
40
60
80
100
120
Efflux (0h) Efflux (24h)
Rho
dam
ine
123
Mea
n Fl
uore
scen
ce In
tens
ity
(%)
Efflux (0h) Efflux (24h)
Chapter 4
128
(A)
(B)
(C)
0.5 µM Mitoxantrone
0
20
40
60
80
100
120
Efflux (0h) Efflux (1h)
Mito
xant
rone
Mea
n Fl
uore
scen
ce In
tens
ity
(MFI
) (%
)
Cou
nt
Mitoxantrone (MX) Fluorescence
Efflux (0h) Efflux (1h)
1 µM Mitoxantrone
0
20
40
60
80
100
120
Efflux (0h) Efflux (1h)
Mito
xant
rone
Mea
n Fl
uore
scen
ce In
tens
ity
(MFI
) (%
)
Cou
nt
Mitoxantrone (MX) Fluorescence
Efflux (0h) Efflux (1h)
0
20
40
60
80
100
120
Efflux (0h) Efflux (1h)
Mito
xant
rone
Mea
n Fl
uore
scen
ce In
tens
ity
(MFI
) (%
)
Cou
nt
Mitoxantrone (MX) Fluorescence
5 µM Mitoxantrone
Efflux (0h) Efflux (1h)
Chapter 4
129
Figure 4.16: Optimisation of mitoxantrone concentration for investigation of ABCG2 efflux activity. MCF-7 cells were incubated with (A) 0.5 µM, (B) 1 µM or (C) 5 µM mitoxantrone for 60 minutes and mitoxantrone mean fluorescence intensity (MFI) was evaluated by flow cytometry at time 0 or following a further 60 minutes of incubation in mitoxantrone-free medium. Mitoxantrone MFI (%) was expressed as a proportion of mitoxantrone fluorescence at 0 h of efflux. Experiments were repeated at least three times and representative results are shown.
Chapter 4
130
020406080
100120
0 15 30 45 60
Mito
xant
rone
Mea
n Fl
uore
scen
t Int
ensi
ty
(MFI
), %
Efflux (min)
Vehicle Control
020406080
100120
0 15 30 45 60
Mito
xant
rone
Mea
n Fl
uore
scen
t Int
ensi
ty
(MFI
), %
Efflux (min)
DHT
020406080
100120
0 15 30 45 60
Mito
xant
rone
Mea
n Fl
uore
scen
t Int
ensi
ty
(MFI
), %
Efflux (min)
Cyclopamine
020406080
100120
0 15 30 45 60Mito
xant
rone
Mea
n Fl
uore
scen
t Int
ensi
ty
(MFI
), %
Efflux (min)
DHT + Cyclopamine
Figure 4.17: DHT and cyclopamine effects on the efflux rate of mitoxantrone from MCF-7 cells. MCF-7 cells which were pre-treated for 8 days with 0.1% (v/v) ethanol (vehicle control), 10-8 M DHT, 2 µM cyclopamine or the combination of 10-8 M DHT and 2 µM cyclopamine were incubated with 1 µM mitoxantrone for 60 minutes then cultured for a further 60 minutes in mitoxantrone-free culture medium during which mitoxantrone fluorescence was evaluated every 15 minutes (0, 15, 30, 45 and 60 minutes). Mitoxantrone mean fluorescence intensity (MFI) (%) was plotted as a ratio of mitoxantrone MFI at time 0 of efflux. Experiments were repeated at least seven times and the mean results ± S.E.M. are shown. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.
40
50
60
70
80
90
100
110
120
0 15 30 45 60Mito
xant
rone
Mea
n Fl
uore
scen
ce
Inte
nsity
(MFI
), %
Efflux (min)
EtOHDHTCyclopamineDHT+Cyclopamine
0
*
*p<0.05
Chapter 4
131
mitoxantrone MFI was progressively decreased to ~80% and ~61% of MFI at time 0
after 15 and 60 minutes, respectively (Figure 4.17). In cells which were pre-treated with
DHT, cyclopamine and the combination of DHT and cyclopamine, the decrease in
mitoxantrone MFI during the 60 minute efflux period was reduced compared to
controls, with intracellular mitoxantrone fluorescence decreased to 94-98% after 15
minutes and 71-75% after 60 minutes (Figure 4.17). These results indicated that DHT
and cyclopamine treatments delayed the export rate of the ABCG2 substrate,
mitoxantrone from MCF-7 cells.
4.2.6.1 DHT and Cyclopamine Effects on the Sensitivity of MCF-7 Cells to
Mitoxantrone
The chemotherapeutic agent, mitoxantrone is a cytotoxic drug which inhibits the
proliferation of rapidly dividing cells by intercalating DNA (Varadwaj et al 2010). As
flow cytometric analyses showed that the efflux of mitoxantrone from MCF-7 cells was
delayed in cells treated with DHT and/or cyclopamine, resulting in higher intracellular
levels of mitoxantrone (Figure 4.17), the responsiveness of cells to mitoxantrone and its
associated cytotoxicity was investigated using MTS viability assays (Section 3.2). For
these studies, a standard curve of cell number against absorbance values of formazan
(490 nm), a soluble dye formed from MTS by viable cells, was constructed in order to
extrapolate cell numbers in experimental culture wells (Figure 4.18).
To investigate DHT and cyclopamine regulation of mitoxantrone cytotoxicity in MCF-7
cells, cells were pre-treated with 10-8 M DHT, 2 µM cyclopamine or 10-8 M DHT + 2
µM cyclopamine for 8 days, then increasing concentrations of mitoxantrone (0.0001-10
µM) were added to the cultures. After 4 days, cell viability estimated using MTS assays
was used to construct mitoxantrone dose-response curves, from which the IC50 values
for mitoxantrone, or the concentration of mitoxantrone that caused 50% inhibition of
cell proliferation, were extrapolated (Section 3.2). The IC50 value for mitoxantrone in
vehicle control (0.1% (v/v) ethanol) MCF-7 cultures was 1.388 µM (Figure 4.19).
Treatment of cells with 10-8 M DHT led to a minor effect on the IC50 values for
mitoxantrone which decreased by ~8% compared to the vehicle control. In contrast, in
cells treated with 2 µM cyclopamine and the combination of DHT and cyclopamine,
mitoxantrone IC50 values were significantly reduced by ~70% compared to the vehicle
control (Figure 4.19). These results indicated that cyclopamine and the combination of
Chapter 4
132
Figure 4.18: Standard curve for MTS proliferation assays. Increasing densities of MCF-7 cells (250 to 30,000 cells) were cultured overnight and cell numbers were quantitated using a CellTiter 96® AQueous One Solution Kit which measures the absorbance of formazan at 490 nm. A standard curve of the average absorbance values from quadruplicate wells (± S.E.M.) against cell seeding densities was constructed, with a trend line fitted through the values. The assay was repeated three times and representative results are shown.
y = 6E-05x + 0.1038 R² = 0.9736
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
0 10000 20000 30000 40000
Abs
orba
nce
at 4
90 n
m
Cells/well
Chapter 4
133
(A)
(B)
Figure 4.19: Sensitivity of MCF-7 cells to mitoxantrone following treatment with DHT and cyclopamine. MCF-7 cells pre-treated with 0.1% (v/v) ethanol (vehicle control), 10-
8 M DHT, 2 μM cyclopamine or 10-8 M DHT + 2 µM cyclopamine for 4 days were incubated with increasing concentrations of mitoxantrone (0-10 μM) and cell viability was measured on day 8 using MTS assays. (A) Dose-response curves of mitoxantrone in DHT and/or cyclopamine-treated MCF-7 cells. (B) IC50 for mitoxantrone extrapolated from the dose-response curves. Experiments were repeated 8 times. Statistical significance was calculated relative to vehicle control by the Mann-Whitney U test, *p<0.05.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
EtOH DHT Cyclop DHT+Cyclop
Mito
xant
rone
IC50
(μM
)
Treatment
10-8 M DHT + 2 µM
Cyclopamine
Vehicle Control
10-8 M DHT 2 µM Cyclopamine
* *
Chapter 4
134
DHT and cyclopamine increased the sensitivity of MCF-7 cells to the cytotoxic effects
of mitoxantrone. Although the efflux rate of mitoxantrone was delayed in DHT-treated
MCF-7 cells, the treatment did not enhance the responsiveness of the cells to
mitoxantrone effects, potentially due to DHT effects on cell cycle progression (Greeve
et al 2004).
4.2.7 Isolation of Breast Cancer Stem-Like Cells from MCF-7 Breast Cancer Cells
Increasing evidence has indicated that resistance of breast cancer stem cells to
therapeutic agents (e.g chemotherapy) is due to overexpression of the ABC transporters,
in particular ABCG2 (Kim et al 2002, Ding et al 2010, Britton et al 2012). To
investigate DHT and cyclopamine regulation of ABCG2 protein expression and
intracellular localisation in breast cancer stem-like cells, subpopulations of cells that
accumulate low levels of the fluorescent ABC transporter substrate, Hoechst 33342 and
express high levels of CD44 and low levels of CD24 (Hoechst 33342lo/CD44hi/CD24lo)
were isolated from the MCF-7 breast cancer cell line by fluorescence-activated cell
sorting (FACS) (Section 3.1.4, 3.5). This subpopulation of cells is reported to function
as cancer stem-like cells and express markers previously characterised as cancer stem
cell markers (Engelmann et al 2008). In initial studies, the concentrations of Hoechst
33342 and antibodies for detection of CD44 and CD24 were optimised using flow
cytometry. For these experiments, MCF-7 cells were incubated with increasing
concentrations of Hoechst 33342 (0.5, 1, 2 or 5 µg/mL) for 60 minutes and Hoechst
33342 fluorescence was detected at two wavelengths, 450 nm (blue) and 650 nm (red)
(Section 3.5; Figure 4.20). In cells incubated with 0.5 µg/mL and 1 µg/mL Hoechst
33342, a Hoechst 33342lo population was not able to be detected as different
populations of cells were not clearly demarcated (Figure 4.20) In contrast, at higher
concentrations of Hoechst 33342 (2 µg/mL and 5 µg/mL), Hoechst 33342lo cells, which
appear as a subgroup of cells at the ‘side’ of Hoechst 33342 (red) vs Hoechst 33342
(blue) plots were evident (Figure 4.20). This was clearest in cells incubated with 5
µg/mL Hoechst 33342, which was used for subsequent studies (Figure 4.20).
To optimise CD44 and CD24 immunostaining, MCF-7 cells were incubated with 1:5
and 1:20 dilutions of allophycocyanin (APC)-conjugated CD44 antibodies (CD44-APC)
or 1:20 and 1:50 dilutions of Brilliant-Violet™ 421-labelled CD24 antibodies (CD24-
BV421) for 30 minutes. At the 1:20 dilution of CD44-APC, a marked overlap between
Chapter 4
135
fluorescence histograms of CD44-APC signals and background fluorescence of
unstained cells, was observed (Figure 4.21A). In contrast, in cells incubated with a 1:5
dilution of CD44-APC, a high proportion of CD44-APC signals did not overlap with
background signals and therefore this antibody dilution was used in subsequent studies
(Figure 4.21A). In cells stained with both 1:20 and 1:50 dilutions of the CD24-BV421
antibody, fluorescence histograms of CD24 did not overlap with background
fluorescence although at the higher concentration (1:20 dilution), a much larger
difference between CD24 and background fluorescence was observed compared to
results in cells incubated with 1:50 CD24-BV421 antibodies (Figure 4.21B). For
experimental studies, the 1:50 dilution of the CD24-BV421 antibody was chosen as this
concentration produced acceptable results. Unfortunately, following co-staining of
MCF-7 cells with 5 µg/mL Hoechst 33342 dye, 1:5 CD44 and 1:50 CD24 antibodies,
spillover of Hoechst 33342 background fluorescence into BV421 detection channels
was observed (Figure 4.21C). As these signals would interfere with identification of
CD24-BV421 fluorescence, a CD24 antibody labelled with a different fluorophore,
phycoerythrin (PE) was used. When MCF-7 cells were incubated with 5 µg/mL Hoechst
33342, 1:5 CD44-APC and 1:5 CD24-PE, there was no spillover of fluorescence or
background signals and therefore the CD24-PE antibody was used in conjunction with
Hoechst 33342 and CD44-APC for subsequent experiments (Figure 4.22).
To isolate Hoechst 33342lo/CD44hi/CD24lo breast cancer stem-like cells from the MCF-
7 breast cancer cell line, MCF-7 cells were cultured in medium containing 5 µg/mL
Hoechst 33342 for 60 minutes, trypsinised then co-stained with 1:5 CD44-APC and 1:5
CD24-PE antibodies for 30 minutes (Section 3.1.4). Breast cancer stem-like cells were
isolated from these cells using a BD Influx™ Cell Sorter (Section 3.5). The MCF-7
population was first gated in FSC vs SSC plots, then single MCF-7 cells were identified
in FSC-height (FSC-H) vs FSC-area (FSC-A) plots (Figure 4.22). By FACS, ~9% of the
single MCF-7 cells were Hoechst 33342lo and 6.4% of these cells expressed high levels
of CD44 and low levels of CD24 (CD44hi/CD24lo), indicating that the Hoechst
33342lo/CD44hi/CD24lo cells constituted ~0.45% of the MCF-7 cell population (Figure
4.22).
To confirm the stem cell-like characteristics of the isolated cells, Hoechst 33342
accumulation, and CD44 and CD24 expression were evaluated by flow cytometry
Chapter 4
136
following culture of the cells for 30 days. During this time period, stem cells and cancer
stem cells have been reported to differentiate into mixed populations including stem-
like cells and non stem-like cells, in this case repopulating the culture with a mixture of
cells similar to that of parental MCF-7 cells (Yin et al 2008). For these assays, the
breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) as well as the Hoechst
33342hi cells, which represent cells with lower levels of expression of ABC transporters
and non cancer stem-like cell characteristics, were isolated from parental MCF-7 cells
using FACS (Section 3.5), then cultured for 30 days. Following 30 days of culture of
the cells, Hoechst 33342lo cells constituted ~11.1% of the total cell population, a result
which was similar to parental MCF-7 cells (Figure 4.23A). However, in the Hoechst
33342lo cell population, 56.6% of the cells were CD44hi/CD24lo, which was
proportionally higher than in parental MCF-7 cells, potentially resulting from an initial
lag in cell proliferation which reduced the number of cell divisions in 30 days of culture
compared to published studies (Figure 4.23). Despite this, the breast cancer stem-like
cells were able to differentiate into non stem-like populations that were absent at day 0
when cells were isolated. These included Hoechst 33342hi cells which constituted 75.6%
of the total population, while in the Hoechst 33342lo subpopulation, 28.4% were
CD44hi/CD24hi, 12.4% were CD44lo/CD24lo and 2.6% of cells were CD44lo/CD24hi
(Figure 4.23). These results indicated that the isolated cells contained stem cell-like
properties as they were capable of giving rise to cells other than those which express the
characteristics of stem cells (CD44hi/CD24lo). In contrast to the breast cancer stem-like
cells, after 30 days of culture of the Hoechst 33342hi cells, only 1.2% of the cells were
Hoechst 33342lo whereas 85.1% of the population was Hoechst 33342hi (Figure 4.23).
None of the Hoechst 33342lo cells was CD44hi/CD24lo, indicating a lack of stem-like
cells within this population.
4.2.7.1 DHT and Cyclopamine Effects on ABCG2 and AR Protein Levels in Breast
Cancer Stem-Like Cells
Following isolation of breast cancer stem cell-like cells, cultures were treated for 8 days
with 10-8 M DHT and/or 2 µM cyclopamine and ABCG2 and AR protein levels were
evaluated by immunoblotting. Due to the low numbers of breast cancer stem-like cells
able to be isolated, mRNA analyses were not carried out for this study. In comparison to
parental MCF-7 cells, ABCG2 protein levels were elevated in the breast cancer stem-
like cells (Figure 4.24A), and following 8 days of 10-8 M DHT treatment, ABCG2
protein expression was decreased by ~37% compared to control breast cancer stem-like
Chapter 4
137
Figure 4.20: Optimisation of Hoechst 33342 concentration for flow cytometry. MCF-7 cells were incubated with 0.5 µg/mL, 1 µg/mL, 2 µg/mL or 5 µg/mL Hoechst 33342 for 60 minutes prior to measurement of Hoechst 33342 fluorescence at 450 nm (blue) and 650 nm (red). Representative results from three independent experiments are shown.
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
0.5 µg/mL Hoechst 33342 1 µg/mL Hoechst 33342
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
2 µg/mL Hoechst 33342
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
5 µg/mL Hoechst 33342
Hoechst 33342lo Hoechst 33342
lo
Chapter 4
138
A (i)
A (ii)
B (i)
CD24-BV421
CD
44-A
PC
CD24-BV21
Cou
nt
1:20 CD24-BV21
Negative Control CD24-BV421
Negative Control
CD24-BV421
CD24-BV421
CD
44-A
PC
CD44-APC
Cou
nt
1:20 CD44-APC Negative Control
CD44-APC
Negative Control
CD44-APC
CD24-BV421
CD
44-A
PC
CD44-APC
Cou
nt
1:5 CD44-APC
Negative Control CD44-APC
Negative Control CD44-APC
Chapter 4
139
B (ii)
(C)
Figure 4.21: Optimisation of CD44-APC and CD24-BV421 antibodies for flow cytometry. MCF-7 cells were stained with (A) APC-conjugated CD44 antibody (CD44-APC) at (i) 1:5 or (ii) 1:20 dilutions or with (B) BV421-conjugated CD24 antibody (CD24-BV421) at (i) 1:20 or (ii) 1:50 dilutions for 30 minutes. Negative controls, which were unstained cells were included to identify background fluorescence. (C) Expression profile of Hoechst 33342, CD44-APC and CD24-BV421 in MCF-7 cells stained with 5 µg/mL Hoechst 33342, 1:5 CD44-APC and 1:50 CD24-BV421.
CD24-BV421
CD
44-A
PC
CD24-BV21
Cou
nt
1:50 CD24-BV21
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
CD24-BV421
CD
44-A
PC
Hoechst 33342 background
Negative Control CD24-BV421
Negative Control CD24-BV421
Hoechst 33342lo
Hoechst 33342hi
Chapter 4
140
(A)
Figure 4.22: Isolation of breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) from MCF-7 cells. MCF-7 cells incubated with 5 µg/mL Hoechst 33342 for 60 minutes were stained with 1:5 CD44-APC and 1:5 CD24-PE for 30 minutes. (A) Forward (FSC) and side scatter (SSC) plots were used to identify the MCF-7 cell population, from which (B) single MCF-7 cells were gated in FSC-H (height) vs FSC-A (area) plots. (C) Low Hoechst 33342-containing cells (Hoechst 33342lo) were identified by measuring Hoechst 33342 fluorescence at two wavelengths, 450 nm (blue) and 650 nm (red), and in this population of cells, cells expressing high levels of CD44 and low levels of CD24 (CD44hi/CD24lo) were isolated using a BD Influx™ Cell Sorter.
FSC
SSC
FSC-A
FSC
-H Single Cells
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
Hoechst 33342lo
Hoechst 33342hi
CD24-PE
CD
44-A
PC
Hoechst 33342lo
Cells
CD44hi/
CD24lo
(B)
(C) (D)
Chapter 4
141
(A)
(B)
Hoechst 33342lo
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
CD24-PE
CD
44-A
PC
Hoechst 33342lo
Cells
CD44hi/
CD24lo
Day 0
Hoechst 33342 (Red) Hoe
chst
333
42 (B
lue)
Hoechst 33342lo
Hoechst 33342hi
CD24-PE
CD
44-A
PC
CD44hi/
CD24lo
Hoechst 33342lo
Cells Day 30
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
Hoechst 33342hi
Day 0
Hoechst 33342 (Red)
Hoe
chst
333
42 (B
lue)
Hoechst 33342lo
Hoechst 33342hi
CD24-PE
CD
44-A
PC
Hoechst 33342lo
CD44hi/
CD24lo
Day 30
Chapter 4
142
Figure 4.23: Confirmation of stem cell properties in MCF-7 breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo). Expression profile of Hoechst 33342, CD44-APC and CD24-PE in (A) Hoechst 33342lo/CD44hi/CD24lo MCF-7 cultures and in (B) Hoechst 33342hi MCF-7 cultures on the day of isolation (Day 0) and 30 days post isolation of cells (Day 30).
Chapter 4
143
cell cultures incubated with 0.1% (v/v) ethanol (Figure 4.24A). A similar DHT-induced
downregulation of ABCG2 levels (~28%) was also evident after 4 days of treatment,
results that were comparable to those detected in DHT-treated parental MCF-7 cells
(Figure 4.4, 4.24A). Co-treatment of the cultures with 10-8 M DHT and 2 µM
cyclopamine for 8 days downregulated ABCG2 protein levels by ~26% compared to the
vehicle control while treatment of MCF-7 stem-like cells with 2 µM cyclopamine
produced small decreases in ABCG2 protein of ~11.7% (Figure 4.24A).
Although AR protein was readily detectable in parental MCF-7 cells, in the breast
cancer stem-like cells, AR protein was barely detectable (Figure 4.24B). However,
following 10-8M DHT treatment of breast cancer stem-like cells for 4 days, AR protein
expression was elevated to ~160% that in parental MCF-7 cells, while after 8 days of
treatment, AR protein expression remained increased at levels that were comparable to
those in parental MCF-7 cells (Figure 4.24B). (AR was not able to be quantitated
against (AR) levels in untreated breast cancer stem-like cells due to the very low
expression of AR in this subpopulation (Figure 4.24B)). AR protein levels are also
reported to be induced in parental MCF-7 cells following DHT treatment, which is in
part due to increased AR protein stability (Greeve et al 2004). In breast cancer stem-like
cells treated for 8 days with 2 µM cyclopamine, AR protein levels remained
undetectable, while 10-8 M DHT and 2 µM cyclopamine co-treatment elevated AR
protein expression to levels ~40% that in parental MCF-7 cells (Figure 4.24B).
4.2.7.2 Intracellular Localisation of ABCG2 in DHT and Cyclopamine Treated
Breast Cancer Stem-Like Cells
DHT and cyclopamine effects on the intracellular localisation of ABCG2 in breast
cancer stem-like cells were evaluated by confocal microscopy using ABCG2 antibodies
and the filamentous actin (F-actin) marker, Phalloidin Red, methods for which had been
optimised previously (Section 4.2.4). ABCG2 staining was diffuse in the nucleus and
cytoplasm of cells and also accumulated in cell-to-cell junction complexes (yellow
arrows) and in round cytoplasmic vesicles (red arrows), similar to its localisation in
parental MCF-7 cells (Figure 4.7, 4.25). Although ABCG2 localisation to these
complexes and vesicles was not quantitated, the numbers of ABCG2-containing cell-to-
cell junction complexes and cytoplasmic vesicles were observed to be higher compared
to parental MCF-7 cells (Figure 4.7, 4.25). ABCG2 also localised to edges of large and
Chapter 4
144
round vesicles (blue arrow) which formed between adjacent breast cancer stem-like
cells and resembled the ABCG2-rich extracellular vesicles (EVs) observed previously in
MCF-7 cells selected for resistance to mitoxantrone (MCF-7/MX) (Figure 4.25) (Goler-
Baron and Assaraf 2011). However, these ABCG2-associated EV-like structures were
not frequently seen in the breast cancer stem-like cell population and were also absent in
parental MCF-7 cells (Figure 4.7, 4.25).
In the breast cancer stem-like cells, the ABCG2-associated cell-to-cell junction
complexes, cytoplasmic (aggresome-like) vesicles and EV-like structures co-localised
with F-actin (Figure 4.25). Treatment of the breast cancer stem-like cells with 10-8 M
DHT, 2 µM cyclopamine or the combination of 10-8 M DHT and 2 µM cyclopamine for
4 days did not alter the localisation or expression of ABCG2 in the EV-like structures
but DHT and DHT/cyclopamine treatments markedly decreased numbers of ABCG2-
containing cell-to-cell junction complexes and cytoplasmic vesicles (Figure 4.25). In
breast cancer stem-like cells treated with 2 µM cyclopamine only, ABCG2 localisation
to cell-to-cell membrane junctions also decreased but ABCG2 accumulation in
cytoplasmic vesicles was increased (Figure 4.25). Interestingly, the cytoplasmic vesicles
in cyclopamine-treated breast cancer stem-like cultures formed as clusters of smaller
vesicles compared to the larger and singular aggresome-like vesicles that had been
observed in control (vehicle-treated) cultures of breast cancer stem-like cells, in parental
MCF-7 cells and in cyclopamine-treated parental MCF-7 cells (Figure 4.25).
Chapter 4
145
(A)
(B)
Figure 4.24: DHT and cyclopamine regulation of ABCG2 and AR protein levels in breast cancer stem-like cells isolated from MCF-7 cultures. Breast cancer stem-like cells (Hoechst 33342lo/CD44hi/CD24lo) isolated from MCF-7 cultures were treated with 10-8
M DHT and/or 2 µM cyclopamine for 8 days prior to protein isolation for immunoblotting. (A) ABCG2 protein levels were increased in MCF-7 stem-like cells in comparison to parental (unsorted) MCF-7 cells and reduced by 4 and 8 days of DHT treatment and 8 days of DHT and cyclopamine treatments. (B) AR levels were barely detectable in MCF-7 stem-like cells but strongly induced in DHT or in DHT and cyclopamine treated cells. Experiments were repeated three times and representative immunoblots are shown.
ABCG2 (70 kDa)
β-actin (44 kDa)
MC
F-7
(Par
enta
l)
MCF-7 (Stem cells)
-
-
+
-
-
+
+
+
+
- DHT Cyclopamine
8days 4days
0
0.5
1
1.5N
orm
alis
ed A
BC
G2
Prot
ein
Lev
els
Treatment
β-actin (44 kDa)
AR (110 kDa)
MC
F-7
(Par
enta
l)
MCF-7 (Stem cells)
-
-
+
-
-
+
+
+
+
- DHT Cyclopamine
8days 4days
0
0.5
1
1.5
2
Nor
mal
ised
AR
Pr
otei
n L
evel
s
Treatment
Chapter 4
146
10-8 M DHT + 2 µM
Cyclopamine
ABCG2 (green)
F-actin (red) ABCG2 + F-actin + Hoechst 33258
2 µM Cyclopamine
10-8 M DHT
Vehicle Control
(0.1% (v/v) ethanol)
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Figure 4.25: Effects of DHT and cyclopamine on the intracellular localisation of ABCG2 in breast cancer stem-like cells isolated from MCF-7 cultures. Breast cancer stem-like cells isolated from MCF-7 cells and seeded onto coverslips were cultured for 4 days in the presence of 10-8 M DHT and/or 2 µM cyclopamine, or 0.1% (v/v) ethanol (vehicle control) prior to immunostaining with ABCG2 primary antibody and Alexafluor® 488-conjugated anti-mouse secondary antibodies (green). Filamentous actin (F-actin, red) was imaged with Phalloidin Red and nuclei (blue) were stained with Hoechst 33258. Negative controls were cells stained with the secondary antibodies only. ABCG2 staining in cell-to-cell junction complexes and in round cytoplasmic vesicles are indicated by yellow and red arrows, respectively. An EV-like structure is indicated by a blue arrow in control cells. Experiments were performed three times and representative results are shown. Scale bar: 30 µM.
Negative Control
ABCG2 (green) Hoechst 33258 (blue) ABCG2 +
Hoechst 33258
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4.3 Discussion
Interaction between the AR and Hedgehog signalling pathways has been reported
previously and in those studies, cross-regulation of the expression of target genes was
observed following activation or inhibition of either pathway (Chen et al 2011a, Sirab et
al 2012b). For example, DHT downregulated the expression of Hedgehog target genes
(e.g. SHH, GLI1, PTCH1) in LNCaP and VCaP prostate cancer cells whilst inhibition of
the Hedgehog pathway was shown to downregulate the mRNA levels of DHT/AR-
mediated target genes (e.g. KLK2, KLK3) in LNCaP cells (Sirab et al 2012b).
Androgens, including DHT have anti-proliferative effects in breast cancer cells and
similarly, the Hedgehog pathway small molecule inhibitor, cyclopamine, has been
shown to inhibit the proliferation of breast cancer cell lines (Greeve et al 2004, Kubo et
al 2004, Zhang et al 2009). In this thesis study, the effects of DHT and cyclopamine
treatments on gene expression were initially evaluated in the ER+ve, PR+ve and AR+ve
breast cancer cell lines, MCF-7 and T-47D by screening the expression of 84 breast
cancer-associated genes using RT2 Profiler Human Breast Cancer PCR Arrays.
Key findings from analysis of the breast cancer PCR arrays included downregulation of
the expression of genes that encode cell cycle regulators (e.g. cyclin D1 (CCND1),
cyclin D2 (CCND2), CDKN1A, JUN, MYC, BCL2) or anti-apoptosis factors (e.g. BCL2,
MYC, JUN) as well as decreased expression of the multidrug resistance (MDR)
transporters, ABCB1 and ABCG2, and regulators of EMT. mRNA levels of cyclin D1
(CCND1), MYC, JUN and BCL2, proteins encoded by which induce cell cycle
progression in breast cancer cells, were downregulated in DHT/cyclopamine co-treated
MCF-7 and T-47D cells. In support of these findings, treatment of MCF-7 cells with
DHT or cyclopamine has been shown to decrease expression of cyclin D1 (Greeve et al
2004, Che et al 2013). Low mRNA expression of MYC, an AR target gene, has been
correlated with increased expression of AR in human breast tumour samples and it was
proposed that AR suppresses MYC expression, a result that is in agreement with DHT-
induced downregulation of MYC observed in the present study (Bieche et al 2001, Gao
et al 2013). Overexpression of JUN in MCF-7 cells has been identified to be a marker
of aggressiveness as it led to increased cell invasion, chemoresistance and loss of
responsiveness of cells to the anti-oestrogen, tamoxifen (Smith et al 1999). Therefore,
downregulation of JUN expression suggests that cellular processes facilitating tumour
progression in addition to cell proliferation are inhibited. GLI1 and AP-1 binding sites
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have been identified in the JUN promoter and downregulation of JUN may be mediated
via inhibition of Hedgehog/GLI signalling in the presence of cyclopamine in the breast
cancer cell cultures (Laner-Plamberger et al 2009). Previously, DHT was found to
decrease BCL2 mRNA and protein expression in MCF-7 cells as well as in the ER+ve,
PR+ve and AR+ve breast cancer cell line, ZR-75-1 (Lapointe et al 1999, Macedo et al
2006). This effect may not be direct as ARE sequences were not able to be identified in
the BCL2 promoter, however an indirect mechanism involving androgen-induced
regulation of the E2F1 transcription factor, which binds to E2F binding sites located in
the BCL2 promoter may mediate androgen effects on BCL2 levels (Huang et al 2004).
Androgens including DHT have been shown in previous studies to inhibit the
proliferation of ER+ve breast cancer cells (MCF-7, T-47D, ZR-75-1) but stimulate the
growth of cell lines which express low to undetectable levels of ER (MDA-MB-231,
MDA-MB-453) (Hackenberg et al 1991, Birrell et al 1995, Greeve et al 2004, Macedo
et al 2006, Ni et al 2011, Barton et al 2015). In this study, treatment of the ER+ve
MCF-7 and T-47D cells with 10-8M DHT inhibited cell proliferation, a result which is
in agreement with previous reports and is associated with the downregulation of
expression of cell cycle and anti-apoptosis genes (Greeve et al 2004, Macedo et al
2006). DHT has been reported to inhibit E2-induced MCF-7 and T-47D cell
proliferation and downregulate ERα transcriptional activity, suggesting that DHT-
induced inhibition of MCF-7 and T-47D cell proliferation by DHT in this study may be
in part mediated via antagonism of the E2/ERα pathway (Peters et al 2009, Need et al
2012).
The Hedgehog pathway inhibitor, cyclopamine is a steroidal alkaloid and teratogen
derived from the corn-lily Veratrum californicum. Cyclopamine specifically binds to
and inhibits SMO by altering its conformation, a similar mechanism to the regulation of
SMO by PTCH1 (Section 1.4.5) (Chen et al 2002). Previous studies have reported that
cyclopamine inhibits the proliferation of both ER+ve (e.g. MCF-7, T-47D, BT-474) and
ER-ve (e.g. SK-BR-3, MDA-MB-231) breast cancer cell lines (Kubo et al 2004,
Mukherjee et al 2006, Zhang et al 2009). This was associated with decreased nuclear
and cytoplasmic levels of GLI1, indicating inhibition of the canonical Hedgehog
signalling pathway. However, most studies have used high concentrations of
cyclopamine (10-20 µM), with MCF-7 and MDA-MB-231 cells reported to be
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unresponsive to cyclopamine concentrations below 20µM, and T-47D cells growth
inhibited only by 10 µM and 20 µM cyclopamine (Mukherjee et al 2006, Zhang et al
2009). At higher concentrations (10-20 µM), cyclopamine-induced growth inhibition
may result from non-specific or SMO-independent effects as the proliferation of both
SMO-expressing and SMO-nonexpressing breast cancer cells is reported to be inhibited
(Zhang et al 2009). In contrast, in the present study, inhibition of MCF-7 and T-47D
cell proliferation was observed at lower concentrations (2 µM) of cyclopamine,
indicating that cultures were more responsive to cyclopamine effects. This may be due
to clonal variation between isolates of the cell lines and differences in study design.
Importantly, treatment of the cells with 2 µM cyclopamine led to downregulation of
GLI1 mRNA levels after 24 h, a result identified in the PCR arrays (data not shown)
which indicates inhibition of Hedgehog signalling.
Co-treatment of MCF-7 and T-47D cells with DHT and cyclopamine also led to
inhibition of cell proliferation. In prostate cancer cells, growth of which is stimulated by
androgens, the combination of an AR inhibitor, pyrvinium pamoate and a Hedgehog
pathway inhibitor, either cyclopamine or LDE225 led to synergistic inhibition of cell
proliferation in vitro and in vivo (Gowda et al 2013). Although there were no marked
differences between the effects on MCF-7 and T-47D cell proliferation of DHT and
cyclopamine co-treatment or treatment with either agent alone, analysis of the RT2
Profiler Human Breast Cancer PCR Arrays indicated that DHT and cyclopamine co-
treatment resulted in regulation of a greater number of genes, most of which were
downregulated. At the present time, there are no published reports on the effects of
DHT and cyclopamine co-treatment on the proliferation of, or gene regulation in breast
cancer cells, and mechanisms underlying the predominant downregulation of gene
expression are currently unknown. Direct interactions between the AR and
Hedgehog/GLI transcription factors have been demonstrated in the prostate cancer cell
line LNCaP and based on these reports, AR-GLI1 interactions in breast cancer cells as
well as binding of the heterodimers to AREs or GLI binding sites resulting in regulation
of the expression of AR, Hedgehog or unique target genes may be investigated in future
studies (Chen et al 2010, Chen et al 2011a).
The AR and Hedgehog pathways modulate cancer cell proliferation and survival, and
are shown to contribute to the development of chemoresistance in multiple types of
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cancers via regulation of the ABC transporters (Cai et al 2007, Ho et al 2008, Singh et
al 2011, Chai et al 2013, Hsieh et al 2013). In the prostate cancer cell line, LNCaP,
DHT increased the mRNA and protein levels of ABCC4, with knockdown of expression
of the transporter by transfection of cells with siRNA-ABCC4 restoring the sensitivity
of LNCaP cells to methotrexate (Cai et al 2007, Ho et al 2008). Overexpression of the
AR in the BFTC 909 upper urinary tract urothelial carcinoma cell line elevated the
expression of ABCG2 and suppressed the cytotoxic effects of doxorubicin in the cells
(Hsieh et al 2013). In the present study, DHT and cyclopamine treatments
downregulated ABCB1 and ABCG2 mRNA expression in both MCF-7 and T-47D cells.
Additional investigation of ABCG2 expression in MCF-7 cells confirmed that DHT and
DHT/cyclopamine co-treatment of the cells downregulated the mRNA and protein
levels of ABCG2.
The expression of ABCB1 in MCF-7 and T-47D cells as well as ABCG2 in T-47D cells
were not further examined in this study due to low endogenous expression of these
transporters, which was evidenced by the high Ct values for ABCG2 in T-47D cells and
ABCB1 in both MCF-7 and T-47D cells. In support of these data, endogenous ABCB1
mRNA and protein expression has been reported as undetectable in previous studies of
MCF-7 cells, and low expression of the ABCG2 protein was also shown in western blot
analysis of ABCG2 in T-47D cells (Imai et al 2005, Calcagno et al 2008, He et al
2013). In future studies investigating ABCB1, experiments may be performed in
ABCB1-overexpressing cells such as following transient or stable expression of
ABCB1 in MCF-7 and T-47D cells. In addition to ABCB1 and ABCG2, at least 16
ABC transporters including ABCC4 and ABCB4 have been reported to be
overexpressed in drug resistant MCF-7 cells (MCF-7/AdVp3000) (Liu et al 2005). As
ABC transporters have overlapping and unique substrates that together influence drug
efflux and drug resistance, comprehensive characterisation of their regulation by
androgens and Hedgehog inhibitors in breast cancer cells will be important for
determining the usefulness of androgen and Hedgehog inhibitor treatments to delay or
prevent drug resistance.
In studies which identified regulation of ABCC4 by the AR, three consensus AREs
were identified 3-6 kb upstream of exon 1 of the ABCC4 sequence (Cai et al 2007).
However, chromatin immunoprecipitation (ChIP) assays did not detect interaction
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between the AR and these AREs in prostate cancer cell lines and it was proposed that
androgen effects may be mediated indirectly via intermediate factors known to regulate
ABCC4 expression such as the ETS variant 1 (ETV1) transcription factor, levels of
which were upregulated by DHT (Sampath et al 2002, Cai et al 2007). As identification
of ARE(s) in the ABCG2 promoter was not performed in this study or reported
previously, it is not known whether the DHT-induced suppression of ABCG2 mRNA
levels involves direct binding of ligand-activated AR to regulatory regions of the
ABCG2 gene. To determine whether DHT effects on ABCG2 expression in MCF-7 cells
were direct, putative AREs in the ABCG2 promoter as well as in the 3’-untranslated
region (UTR) of DNA sequences may be investigated in future studies.
Direct effects of oestrogens and progesterone, but not androgens, on the expression of
ABCG2 in breast cancer cells have been reported previously (Ee et al 2004a, Imai et al
2005, Yasuda et al 2006, Yasuda et al 2009). Oestrogen (ERE) and progesterone (PRE)
responsive elements were identified in the ABCG2 promoter, and oestrogen- or
progesterone-mediated modulation of ABCG2 mRNA and protein expression was
shown to involve ligand-induced binding of ER and PR to their respective DNA binding
sites in the ABCG2 promoter (Ee et al 2004b, Wang et al 2008b). As DHT antagonises
E2/ERα-induced MCF-7 and T-47D breast cancer cell proliferation and ERα target
genes in part by direct interaction between the AR and ERα and binding of the AR to an
ERE, it is possible that the downregulation of ABCG2 expression by DHT is mediated
via indirect mechanisms involving inhibition of the ERα signalling pathway (Panet-
Raymond et al 2000, Peters et al 2009, Need et al 2012).
The role of Hedgehog signalling in the overexpression of ABCG2 has been investigated
using diffuse large B-cell lymphoma (DLBCL) cells, identifying a GLI binding site
~408 bp upstream of the ABCG2 transcriptional start site (Singh et al 2011). Inhibition
of the Hedgehog pathway by the synthetic inhibitor, KAAD-cyclopamine decreased
ABCG2 mRNA levels in the DLBCL cell lines, SUDHL2, OCI-LY10, BJAB and
DOHH2, indicating that Hedgehog signalling in part regulates steady state ABCG2
levels (Singh et al 2011). However, in the present study, cyclopamine treatment on its
own had little to no effects on ABCG2 mRNA and protein levels in MCF-7 cells.
Although further studies will be required to characterise the cell type-specific effects of
Hedgehog signalling on the regulation of ABCG2 levels, these effects may be due to the
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differential expression of GLI/Hedgehog cofactors in different cell types (Kasper et al
2006). In contrast to findings in this thesis, KAAD-cyclopamine was recently reported
to downregulate ABCB1 and ABCG2 mRNA levels in MCF-7 cells (Das et al 2013).
The discordant results may have resulted from the higher concentration of KAAD-
cyclopamine (10 µM) used in that study (Das et al 2013). KAAD-cyclopamine has also
been reported to exhibit greater potency compared to natural cyclopamine, inhibiting
Hedgehog signalling activity to levels similar to that with cyclopamine but at lower
concentrations (Taipale et al 2000).
ABCG2 functions as a drug efflux transporter when bound to the plasma membrane of
cells (Robey et al 2007, Nakanishi 2012). Decreased ABCG2 localisation to the
membrane and retention of ABCG2 in the cell cytoplasm have been shown to impede
ABCG2 efflux activity and increase sensitivity of cells to cytotoxic drugs exported by
ABCG2 (Mizuarai et al 2004, Robey et al 2007, Nakanishi 2012, To and Tomlinson
2013). In the present study, DHT and cyclopamine treatments of MCF-7 cells decreased
ABCG2 levels in cell-to-cell junction complexes, with cyclopamine treatment alone
also shown to induce accumulation of ABCG2 into cytoplasmic vesicles. These findings
suggested that DHT and cyclopamine were inhibiting ABCG2 function and in support
of this hypothesis, DHT, cyclopamine and the combination of both agents were shown
to delay efflux of the ABCG2 substrate, mitoxantrone from MCF-7 cells, which resulted
in increased sensitivity of cells to mitoxantrone-induced cytotoxic effects.
The identity of the ABCG2-containing cytoplasmic vesicle is currently unclear.
However, these vesicles resembled aggresomes in which aggregates of proteins that
have been tagged for degradation are accumulated (Garcia-Mata et al 2002,
Wakabayashi et al 2007, Zaarur et al 2014). Previous studies have identified that
histone deacetylase 6 (HDAC6) forms bridges between ubiquitinated protein aggregates
and dynein motors, which transport the protein cargo along microtubules towards the
microtubule organising centre (MTOC) for development of aggresomes (Garcia-Mata et
al 2002, Kawaguchi et al 2003). Disruption of the microtubules prevents aggresome
formation (Garcia-Mata et al 1999, Kawaguchi et al 2003). Hence, to investigate
whether the ABCG2-containing cytoplasmic vesicles are aggresomes, experiments
using aggresome specific markers such as HDAC6 and treatment of MCF-7 cells with
nocodazole, an inhibitor of polymerisation of microtubules, may be performed (Garcia-
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Mata et al 1999, Kawaguchi et al 2003). In a recent study, ABCG2 protein in pancreatic
ductal adenocarcinoma (PDAC) cells was reported to localise in the membranes of large
and round autofluorescent compartments, which resembled the ABCG2-associated
cytoplasmic vesicles identified in MCF-7 cells (Miranda-Lorenzo et al 2014). The
autofluorescence was attributed to accumulation of the naturally fluorescent ABCG2
substrate, riboflavin into these compartments, formation of which was dependent on
ABCG2 expression and activity as autofluorescence was abolished by treatment of the
cells with the ABCG2 inhibitor, fumitremorgin C (FTC) (Miranda-Lorenzo et al 2014).
Only a minor proportion of the PDAC-derived cells expressed the autofluorescent
compartments, a feature that is similar to the frequency of ABCG2-containing vesicles
in MCF-7 cells, and the autofluorescent but not non-autofluorescent cells were shown to
form tumours in mice and possess stem cell-like characteristics by generating both
autofluorescent and non-autofluorescent cells in vitro (Miranda-Lorenzo et al 2014). As
such, the ABCG2-containing cytoplasmic vesicles may be a characteristic of cancer
stem cells, which is consistent with the higher numbers of ABCG2-containing vesicles
in the breast cancer stem-like cells observed in the present study.
Localisation of Lysotracker Red around ABCG2-containing cytoplasmic vesicles in
MCF-7 cells was similar to previous findings where lysosome clustering around
aggresomes was shown to be important for lysosomal degradation of proteins in the
aggresomes (Zaarur et al 2014). These findings therefore suggested that the ABCG2-
containing cytoplasmic vesicles may be degraded by the lysosomes. However, it was
difficult to strongly support this hypothesis by western blot analysis of chloroquine
effects on ABCG2 protein levels in DHT and cyclopamine treated MCF-7 cells as
results were not prominent and were difficult to reliably reproduce. To confirm these
results, other inhibitors of the lysosome (e.g. ammonium chloride, bafilomycin A1) may
be evaluated in future studies to investigate DHT and cyclopamine regulation of
ABCG2 expression. The lack of reproducibility of western blot analysis of lysosome-
mediated degradation of ABCG2 may also be attributed to activation of secondary
degradation pathways to compensate for loss of the lysosomal pathway or recycling of
ABCG2 between the cell membrane and cytoplasmic organelles/vesicles, which can
occur following de-ubiquitination of proteins (Studzian et al 2015). For example,
ubiquitin-specific processing protease Y (UBPY)/USP8, a de-ubiquitinating enzyme has
been shown to decrease levels of ubiquitinated EGFR and delay proteasomal
degradation of EGFR (Mizuno et al 2005).
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Diffuse staining of ABCG2 was detected in the cytoplasm and nucleus of MCF-7 cells,
with nuclear localisation of ABCG2 confirmed by subcellular fractionation studies.
Cytoplasmic and nuclear localisation of ABCG2 have been reported in drug resistant
MCF-7 cells (MCF-7/Advrp3000) but not in parental MCF-7 cells (Litman et al 2000).
Although nuclear localisation of ABCG2 has been documented in multiple cell types
including head and neck squamous cell carcinoma and glioblastoma multiforme cells,
functional studies of nuclear ABCG2 are limited (Chen et al 2006, Bhatia et al 2012).
Recently, ABCG2 was shown to exhibit transcription factor-like functions in the
nucleus of A549 human lung carcinoma cells and induced transcription of E-cadherin
through binding to the E-box of the CDH1 (E-cadherin) promoter (Liang et al 2015).
MCF-7 cells are AR+ve breast cancer cell lines and AR protein levels have been shown
to increase following DHT treatment (Greeve et al 2004, Chua 2011). Interestingly, in
this study, AR protein expression in breast cancer stem-like cells derived from the
MCF-7 breast cancer cell line was not able to be detected by western blotting, although
DHT treatment of these cells markedly induced expression of AR protein. This
suggested that the very low levels of AR expression in breast cancer stem-like cells
were below detection limits of the AR antibody. AR expression in breast cancer stem
cells has not been reported previously but low levels of the AR have been documented
in stem cells of benign and malignant prostate tissues (Fedoruk et al 2004, Huss et al
2005). Previously, oestrogens and progesterone have been reported to increase the
proportion of breast cancer stem cells, promoting the formation of breast tumours
(Vares et al 2013). In stem cells of luminal breast cancer cell lines (e.g. MCF-7 and T-
47D) as well as normal mammary gland stem or progenitor cells, expression of ER and
PR were low. Despite this, the breast cancer stem cells were capable of responding to
oestrogens and progesterone in a paracrine manner resulting from interactions with
ER+ve and PR+ve breast cancer cells in the cell population (Asselin-Labat et al 2010).
Hence, DHT-induced upregulation of AR protein levels in cultures of MCF-7-derived
breast cancer stem-like cells may similarly involve paracrine activation of AR signalling
in the breast cancer stem-like cells by rare AR+ve cells that may be present in the
cultures. This may be investigated by AR immunofluorescence or confocal microscopy
of MCF-7 stem cell-like cells.
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ABC transporters are implicated in the resistance of cancer stem cells to therapeutic
drugs, which potentially leads to tumour relapse and progression (Lou and Dean 2007,
Robey et al 2007). In the present study, DHT and DHT/cyclopamine treatment of breast
cancer stem-like cells markedly downregulated ABCG2 protein levels and ABCG2
localisation in cell-to-cell junction complexes and cytoplasmic vesicles. Cyclopamine
treatment of the breast cancer stem-like cells also stimulated the accumulation of
ABCG2 in cytoplasmic vesicles and interestingly, these vesicles were observed as
clusters of small vesicles unlike the larger and single ABCG2-containing vesicles seen
in parental MCF-7 cells. As it is possible that these smaller vesicles fuse to form large
vesicles, real time fluorescence microscopy may be performed to investigate formation
of ABCG2 cytoplasmic vesicles in the breast cancer stem-like cells. Based on results
obtained using parental MCF-7 cells, DHT- and/or cyclopamine-induced decreases in
ABCG2 protein expression and localisation in cell-to-cell junction complexes suggest
that the treatments also inhibit ABCG2 efflux function in the breast cancer stem-like
cells. To investigate this hypothesis, flow cytometry and MTS viability assays may
similarly be performed to determine DHT and cyclopamine regulated efflux of ABCG2
substrates and sensitivity of the breast cancer stem-like cells to chemotherapeutic
agents.
In breast cancer stem-like cell cultures, a small population of the cells also expressed
round ABCG2-associated vesicles between adjacent cells. These vesicles resembled
extracellular vesicles (EVs) previously documented in MCF-7 cells selected for
resistance to mitoxantrone (MCF-7/MX) which express high levels of ABCG2 (Ifergan
et al 2005, Goler-Baron and Assaraf 2011). Therefore, it is possible that the elevated
levels of ABCG2 protein in the MCF-7 derived breast cancer stem-like cells induced
formation of the EV-like structures. ABCG2-associated EVs were also reported to
sequester a number of ABCG2 substrates including mitoxantrone, topotecan and
methotrexate, resulting in drug resistance (Ifergan et al 2005, Goler-Baron and Assaraf
2011). Immunofluorescence or confocal microscopy may be performed to determine
whether ABCG2 substrates are similarly sequestered into the EV-like structures in the
breast cancer stem-like cells. Although DHT and cyclopamine treatments did not
markedly alter ABCG2 levels in the EV-like structures, DHT and cyclopamine effects
on drug sequestration in the EV-like structures may also be investigated.
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Initial findings from this thesis demonstrated that DHT and cyclopamine treatments of
MCF-7 and T-47D cells downregulated the expression of genes that encode cell cycle
regulators, anti-apoptosis factors, ABC drug transporters and EMT-associated factors.
Further investigation of DHT- and cyclopamine-induced regulation of ABCG2
identified decreased ABCG2 protein expression and reduced localisation of ABCG2 in
cell-to-cell junction complexes in both MCF-7 cells and breast cancer stem-like cells
isolated from MCF-7 cultures. In MCF-7 cells, reduced ABCG2 expression at the
plasma membrane was correlated with increased intracellular accumulation of the
ABCG2 substrate, mitoxantrone and increased sensitivity of MCF-7 cells to the
cytotoxic effects of mitoxantrone. Based on preliminary experiments that screened
regulation of gene expression in DHT and cyclopamine treated MCF-7 cells (Section
4.2.1), subsequent studies investigated DHT and cyclopamine effects on EMT.
Chapter 5
DHT AND CYCLOPAMINE REGULATION OF
EMT IN MCF-7 AND T-47D CELLS
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5.1 Introduction
Metastatic disease is a major cause of breast cancer-associated death and although
treatment of early stage breast tumours is initially successful, ~30% of patients develop
distant metastases while 4-10% of patients present with metastatic disease (Cardoso et
al 2012, Purushotham et al 2014). EMT is an important physiological programme
which has been shown to facilitate cancer cell migration, invasion and metastasis via the
co-ordinated regulation of expression of genes that encode regulators or components of
cell-to-cell adhesion complexes, cell-to-ECM interactions, secretion and deposition of
ECM components, re-organisation of the ECM and actin cytoskeleton, migration,
production of proteases (e.g. MMP) and invasion. The EMT process is driven by
activation of major pro-EMT signalling pathways, including the TGFβ, WNT and
NOTCH pathways (Section 1.7), while a number of modulators of the expression and/or
activity of central EMT or EMT-associated processes influence initiation or progression
of EMT, for example, steroid hormones and microRNAs (miRNAs) (Wu and Zhou
2008).
Oestrogens and ERα stimulate EMT in ERα-expressing breast cancer cells, and
treatment of MCF-7 and T-47D cells with E2 has been reported to decrease expression
of E-cadherin and upregulate vimentin levels, indicating induction of an EMT
programme (Jimenez-Salazar et al 2014, Sun et al 2014). (Jimenez-Salazar et al 2014,
Sun et al 2014). These effects were reversed by fulvestrant, an ER antagonist,
supporting involvement of E2/ER signalling in the promotion of EMT (Jimenez-Salazar
et al 2014). Loss of E-cadherin expression has been associated with E2-mediated re-
organisation of the actin cytoskeleton and formation of lamellipodial structures which
facilitate cell migration (DePasquale 1999). MCF-7 and T-47D cells undergo
transformation to motile mesenchymal-like or spindle-shaped cells following treatment
with E2, which also downregulates expression of the epithelial marker, occludin and
induces nuclear localisation of the tight junction proteins, zona occludens 1 (ZO-1) and
ZO-1-associated nucleic acid binding (ZONAB), thereby disrupting tight junctions and
facilitating cell migration (Jimenez-Salazar et al 2014, Sun et al 2014). E2/ER-induced
EMT was also found to involve GLI1 activation that was independent of the canonical
Hedgehog signalling pathway as the small molecule Hedgehog pathway inhibitor,
cyclopamine did not inhibit E2-induced activation of GLI1 (Sun et al 2014).
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In more aggressive and metastatic ER-ve breast tumours, the absence of ERα expression
has been proposed to lead to activation of EMT (Al Saleh et al 2011, Iseri et al 2011).
Although oestrogens and ERα promote the proliferation, migration and invasion of
ER+ve breast cancer cells, ERα maintains a more epithelial phenotype of ER+ve breast
cancers. Metastasis tumour antigen 3 (MTA3), a component of the transcriptional
repressor complex, Mi2/NuRD, is transcriptionally activated by E2/ERα signalling and
downregulates expression of the EMT-inducing transcription factor, SNAI1, inhibiting
EMT (Fujita et al 2003). In that study, it was hypothesised that low expression of
MTA3 in ER-ve breast cancers may be a mechanism by which EMT and tumour
metastasis are promoted in these cancers (Fujita et al 2003). The role of E2/ERα
signalling in promoting proliferation and migration but maintaining an epithelial
phenotype of ER+ve breast cancers as opposed to the activation of EMT in ER-ve
breast tumours therefore suggests that EMT is differentially regulated by E2/ERα
signalling in breast tumours according to the level of ERα expression.
Progesterone and PR signalling inhibit or reverse EMT in several types of malignancies
including breast and endometrial cancers (Zuo et al 2010, van der Horst et al 2012). In
PR-ve breast cancer, in which loss of PR expression was postulated to facilitate EMT
and tumour metastasis, progesterone treatment or re-activation of PR signalling reversed
EMT (Zuo et al 2010). In the basal-like breast cancer cell line, MDA-MD-468 (ER-
ve/PR-ve/HER2-ve), progesterone was shown to upregulate expression of epithelial
markers, including occludin and E-cadherin, and downregulate SNAI1 protein
expression, indicating reversal of EMT (Zuo et al 2010). MDA-MB-468 cells lack
expression of cytoplasmic and nuclear PR, and this study provided evidence that
progesterone effects on EMT were mediated via non-genomic PR signalling involving
membrane-associated PRα (mPRα), which is capable of activating secondary pathways
such as the MAPK or ERK1/2 pathways (Zhu et al 2003, Zuo et al 2010). In
endometrial cancer, canonical PR signalling is involved in mediating progesterone
effects on EMT. In the Ishikawa (IK) endometrial cancer cell line transfected with PRB,
treatment with progesterone or the synthetic progestin, medroxyprogesterone acetate
(MPA) reduced cell migration, vimentin expression and expression of IL6, TGFβ and
WNT signalling intermediates, indicating reversal of EMT (van der Horst et al 2012).
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Due to the significance of the androgen/AR axis in prostate carcinogenesis and tumour
growth, studies on androgen/AR regulation of EMT have been focussed on prostate
cancer and progression to castrate-resistant prostate tumours (Wang et al 2008a, Zhu
and Kyprianou 2010). DHT treatment of the LNCaP prostate cancer cell line has been
shown to downregulate E-cadherin levels and in the low AR+ve prostate cancer cell
line, PC-3, in which AR levels are stimulated by DHT, E-cadherin levels also decreased
and N-cadherin expression was upregulated following DHT treatment, indicating
activation of EMT (Zhu and Kyprianou 2010). Prostate tumours are commonly treated
with androgen ablation therapies, but development of androgen-independent (castrate-
resistant) tumours frequently occurs and is associated with tumour progression and
metastasis. This is also reported to be correlated with activation of EMT (Jennbacken et
al 2010, Zhu and Kyprianou 2010, Sun et al 2012). For example, N-cadherin levels are
higher in androgen-independent LNCaP-19 prostate tumours grown as xenografts in
mice compared to androgen-dependent LNCaP tumours (Jennbacken et al 2010).
Similarly, E-cadherin levels were decreased but expression of the EMT-inducing
transcription factors, ZEB1, ZEB2 and TWIST1 was increased in LuCaP35 prostate
tumours growing in castrated mice in comparison to prostate tumours growing in intact
mice (Sun et al 2012).
In breast cancer, androgens have been shown to promote EMT in both ER-ve and
ER+ve breast cancer cells. The molecular apocrine breast cancers lack expression of ER
and PR but express the AR, while a proportion of ER-ve/PR-ve/HER2-ve triple-
negative breast cancers (TNBC) are also AR+ve (Section 1.4.4.3) (Moinfar et al 2003,
Safarpour et al 2014). In in vitro models of ER-ve/PR-ve breast tumours, such as the
AR+ve MDA-MB-453 cell line, treatment with the AR inhibitor, enzalutamide inhibited
cell proliferation and knockdown of AR expression similarly decreased cell
proliferation as well as inhibiting anchorage-independent growth of cells, cell migration
and cell invasion (Cochrane et al 2014, Barton et al 2015). The TNBC cell line, MDA-
MB-231 expresses very low levels of AR but AR nuclear localisation was inducible
following DHT treatment (Barton et al 2015). DHT was shown to stimulate ZEB1
expression as well as migration of MDA-MB-231 cells and these effects were reversed
by the anti-androgen, bicalutamide, indicating that androgens and the AR stimulate
EMT in ER-ve/PR-ve breast cancers (Graham et al 2010). In the ER+ve, PR+ve, and
AR+ve breast cancer cell lines, MCF-7 and T-47D, DHT but not the synthetic
androgen, R1881 has been shown to stimulate cell migration and to also reduce E-
Chapter 5
161
cadherin mRNA expression (Liu et al 2008, Zhu and Kyprianou 2010). Furthermore,
DHT was reported to induce AR binding to regulatory sequences in the E-cadherin
promoter, indicating direct regulation of E-cadherin expression (Liu et al 2008).
In addition to the steroid hormones, miRNAs, cytokines (e.g. tumour necrosis factor
alpha (TNFα)), growth factors (e.g. HGF, EGF) and their associated pathways, and
Hedgehog, WNT and NOTCH signalling also modulate EMT by altering the expression
of EMT regulators as well as mediators of cell migration and invasion (Lo et al 2007,
Gregory et al 2008, Fiaschi et al 2009, Li et al 2012). miRNAs are non-coding RNAs
that regulate gene expression at the post-transcriptional level by inhibiting protein
translation or inducing mRNA degradation (Wang and Zhou 2013). Both miRNA-
mediated stimulatory and inhibitory effects on breast cancer metastasis have been
reported, with members of the miR-200 family (miR-200a, miR-200b, miR-200c, miR-
141 and miR-429) and miR-205 antagonising EMT (Gregory et al 2008, Kong et al
2008, Korpal et al 2008). In support of this, expression of the miR-200 family members
and miR-205 were lower in normal murine mammary gland (NMuMG) cells treated
with TGF-β1 which induced EMT by downregulating E-cadherin expression,
upregulating levels of ZEB1 and N-cadherin, and promoting cell migration (Gregory et
al 2008, Korpal et al 2008). In contrast, overexpression of miR-200a, miR-200b and
miR-429 in TGF-β1-treated NMuMG and mesenchymal-like 4TO7 mammary
carcinoma cells reversed TGF-β1-induced EMT, indicating the inhibitory effects of
miR-200 family members on EMT (Gregory et al 2008, Korpal et al 2008).
Other miRNAs which facilitate EMT and EMT-associated cell migration and invasion
include miR-155, miR-9 and miR-10b (Ma et al 2007, Gregory et al 2008, Kong et al
2008). Expression of miR-155 is elevated in NMuMG cells following TGF-β1
treatment, whereas knockdown of miR-155 expression in TGF-β1-treated NMuMG
cells reversed TGF-β1-induced effects on EMT such as the downregulation of E-
cadherin levels and disruption of E-cadherin-associated tight junctions (Kong et al
2008). In the SUM-149 breast cancer cell line, overexpression of miR-10b increased in
vitro cell invasion and inhibited the translation of HOXD10 mRNA, resulting in
increased expression of regulators of cell migration and extracellular matrix remodelling
(e.g. RHOC, ITGA3, MMP14, urokinase-type plasminogen activator receptor (uPAR)),
thereby promoting an EMT programme (Ma et al 2007). Supporting this mechanism,
Chapter 5
162
transplantation of SUM-149 cells transfected with miR-10b into the mammary fat pad
of mice led to increased tumour invasion (Ma et al 2007).
TNF-α is a cytokine that has important roles in the regulation of inflammation and cell
homeostasis, and is also involved in tumour progression (Balkwill 2009). TNFα/TNFα
receptor 1 (TNFR1)-mediated activation of TNF receptor-associated factor (TRAF2)
recruits inhibitor of kappa B (IκB) kinase (IKK) to phosphorylate IκB, preventing its
binding and sequestration of the NFκB transcription factor (Wu and Zhou 2010). As a
result, release of NFκB leads to its nuclear localisation, where it binds to consensus
sequences (κB sites) to transcriptionally activate genes (Wang and Zhou 2013). Several
experimental studies have provided evidence that TNF-α is able to induce EMT in
breast cancer cells via activation of NFκB signalling. Treatment of the nonmalignant
breast epithelial cell line, MCF10A and the breast cancer cell line, BT-549 with TNF-α
resulted in transcriptional upregulation of TWIST1 via p56, a downstream target of
NFκB signalling (Li et al 2012). TWIST1 was also required for TNFα-induced EMT as
knockdown of TWIST1 expression in MCF10A cells led to decreased expression of N-
cadherin, fibronectin, TWIST1 and upregulation of E-cadherin, indicating inhibition of
EMT (Li et al 2012).
Growth factors such as hepatocyte growth factor (HGF), epidermal growth factor (EGF)
and fibroblast growth factors (FGF) regulate cell survival, proliferation, migration and
invasion following interaction with their cognate receptor tyrosine kinases (RTKs) and
activation of RAS signalling which transduces signals from RTKs (Wang and Zhou
2013). For example, EGF and transforming growth factor α (TGFα) induced a more
mesenchymal-like phenotype in the MDA-MB-468 breast cancer cell line, which was
associated with elevated expression of TWIST1 mRNA and protein, an important EMT
regulator (Lo et al 2007). In addition, activation of MAPK signalling in HEK293 and
MCF10A cells by transfection of RAS or treatment with TGF-β1 stimulated
phosphorylation of TWIST1 at serine 68 (S68), which is known to stabilise and protect
TWIST1 from ubiquitination and degradation (Hong et al 2011). This results in
increased expression of TWIST1, promoting TWIST1-induced EMT, which was
associated with downregulation of the expression of epithelial markers, E-cadherin, β-
catenin and γ-catenin, increased expression of vimentin, and increased cell invasion
(Hong et al 2011).
Chapter 5
163
Aberrant activation of the Hedgehog signalling pathway is a major cause of cancer cell
proliferation, survival, migration and invasion that may be in part mediated via EMT.
Overexpression of GLI1 in immortalised human pancreatic ductal epithelial cells
promoted invasion and markedly downregulated E-cadherin expression, while
inhibition of Hedgehog pathway signalling in the E3LZ10.7 pancreatic cancer cell line
decreased SNAI1 but upregulated E-cadherin mRNA levels, which are indicative of
inhibition of EMT (Feldmann et al 2007). In the mouse mammary gland, ectopic
expression of Gli1, which led to formation of hyperplastic lesions and breast tumour
development, also induced EMT-like characteristics (Fiaschi et al 2009). In that model,
levels of E-cadherin, which was expressed on baso-lateral surfaces of alveolar and
ductal epithelial cells in the mammary glands of wild-type mice, were markedly
downregulated in hyperplastic regions or ductal tumours of Gli1-overexpressing mice
where a large proportion of cells expressed SNAI1 (Fiaschi et al 2009). Paracrine
Hedgehog signalling involving tumour and stromal cell interactions is also important in
inducing stroma-mediated tumour growth and metastasis of breast cancers and other
cancers (Section 1.4.5.1). Transplantation of GLI2-transfected MDA-MB-231 cells into
mice has been shown to induce formation of osteolytic bone metastases in the femora or
tibiae of mice (Sterling et al 2006, Johnson et al 2011). In other cancers such as
pancreatic cancer, formation of liver metastases, which was inhibited by the Hedgehog
pathway antagonist, AZD8542, was observed in mice injected with both the BxPC3
pancreatic cancer cells and pancreatic cancer associated fibroblasts but not in mice
injected with BxPC3 cells only, indicating the involvement of paracrine Hedgehog
signalling in the metastasis of pancreatic tumours to the liver (Hwang et al 2012).
In this study, analysis of results from RT2 Profiler Human Breast Cancer PCR Arrays
identified downregulation of expression of genes associated with EMT in MCF-7 and
T-47D cells treated with DHT, cyclopamine or co-treated with DHT and cyclopamine
(Section 4.2.1). These findings were further investigated using RT2 Profiler EMT PCR
Arrays, which screened expression of 84 EMT-associated genes. As the EMT process
alters migration and invasion of cancer cells, the effects of DHT, cyclopamine and
DHT/cyclopamine treatments on the migration and invasion of MCF-7 cells were
evaluated to support bioinformatics predictions based on results of the EMT PCR
Arrays.
Chapter 5
164
5.2 Results
Analysis of results from RT2 Profiler Human Breast Cancer PCR Arrays (Section 4.2.1)
indicated that expression of the EMT regulators, TGFB1, SRC and NOTCH1, and the
EMT transcription factors, TWIST1 and SNAI2 were downregulated following 24 h of
treatment of MCF-7 and T-47D cells with 10-8 M DHT and/or 2 µM cyclopamine. The
decreased expression of these genes, which encode promotors of EMT suggested that
DHT and cyclopamine may reverse EMT and potentially drive an MET-like process,
inhibiting cell migration, invasion and cancer metastasis (Yilmaz and Christofori 2009).
In this study, DHT and cyclopamine regulation of EMT was further investigated using
RT2 Profiler Human EMT PCR Arrays which screened the expression of 84 EMT-
associated genes (Figure 3.1, Appendix 2). These analyses were again performed
following 24 h of 10-8 M DHT and/or 2 µM cyclopamine treatments of MCF-7 and T-
47D cells.
5.2.1 DHT and Cyclopamine Regulation of EMT-Associated Genes in Breast
Cancer Cells
Prior to studies using the RT2 Profiler Human EMT Arrays, androgen receptor (AR)
qPCR was performed to verify cDNA quality and to confirm the previously determined
effects of DHT and cyclopamine treatments on AR gene expression in MCF-7 and T-
47D cells. For this study, efficiency curves for AR and the housekeeping gene, GAPDH,
were initially constructed by amplification of the genes of interest in serial dilutions of
cDNA derived from MCF-7 and T-47D cells (Section 3.8.7). Efficiencies for AR and
GAPDH qPCR were between 95 and 101% in both the MCF-7 and T-47D cells (AR:
100.6% and 96.6% in MCF-7 and T-47D, respectively, and GAPDH: 95.8% and
101.4% in MCF-7 and T-47D cells, respectively) with correlation coefficient values
(R2) of the linear curves close to 1 (0.97-0.99) (Figure 5.1). Similar to results obtained
during my Honours project and in previous studies carried out in the laboratory, AR
mRNA levels were downregulated following DHT treatment and DHT/cyclopamine co-
treatment, while cyclopamine had little effects on AR levels (Figure 5.2).
To evaluate DHT and cyclopamine induced changes in the expression of genes
encoding regulators or effectors of EMT, RNA isolated from MCF-7 and T-47D cells
which had been treated for 24 h with 10-8 M DHT, 2 µM cyclopamine or a combination
of 10-8 M DHT and 2 µM cyclopamine (Section 3.8.1) was reverse transcribed (Section
Chapter 5
165
3.8.2.2) and added with RT2 SYBR Green Master Mix to 384 array plates that contained
primers for 84 EMT-associated genes (Section 3.8.8). qPCR was performed using a
Roche Light Cycler® 480 with threshold cycle (Ct) values derived from amplification
curves identifying 10 genes in both MCF-7 and T-47D cells which had Ct values of 0 or
40 cycles, indicating low or undetectable expression of these genes (Appendix 3, 4, 5,
Figure 5.3, 5.4). These included genes associated with cell invasion in MCF-7 cells such
as the ECM component, collagen 1 alpha 2 (COL1A2) as well as the matrix
metalloproteinases, MMP2 and MMP3, which degrade the ECM to facilitate cell
migration and invasion into the ECM. MMP2 gene expression was also undetectable in
T-47D cells, which may be due to the non-invasive characteristics of the MCF-7 and T-
47D cell lines. A study by Nawrocki Raby et al has similarly reported undetectable
levels of MMP2 mRNA in MCF-7 and T-47D cells (Nawrocki Raby et al 2001).
PDGFRB levels were also low in T-47D cells, in addition to SNAI2, bone
morphogenetic 2 (BMP2), forkhead box protein C2 (FOXC2) and caveolin 2 (CAV2)
(Figure 5.3 and 5.4).
Ct values of genes expressed in the cell lines were deposited into the SABiosciences
web-based data analysis programme to normalise gene expression to an average of the 5
housekeeping genes, ACTB, B2M, GAPDH, HPRT1 and RPLP0, and to calculate their
expression relative to control cultures treated with 0.1% (v/v) ethanol (vehicle) (Section
3.8.8, Appendix 4, 5). By setting the fold regulation threshold to 1.5-fold, a total of 31
genes were either up- or downregulated in MCF-7 cells cultured with any of the
treatments, while 56 genes were differentially expressed in DHT and/or cyclopamine
treated T-47D cells, with the affected genes predominantly downregulated (Figure 5.3,
5.4). In MCF-7 cells, DHT upregulated expression of 12 genes and decreased
expression of 11 genes, cyclopamine upregulated expression of 8 and downregulated
expression of 7, while DHT and cyclopamine co-treatment upregulated expression of 11
and downregulated expression of 9 genes (Figure 5.3). In T-47D cells, DHT upregulated
expression of 3 genes and downregulated expression of 34 genes, cyclopamine
upregulated expression of 2 and downregulated expression of 39, while DHT and
cyclopamine co-treatment upregulated expression of 4 and downregulated expression of
35 genes (Figure 5.4).
Chapter 5
166
Expression of the EMT or mesenchymal markers, SNAI1, TWIST1 and vimentin (VIM)
were downregulated in T-47D cells treated with DHT and/or cyclopamine (Figure 5.4).
The N-cadherin gene, CDH2, which is upregulated during EMT, was also
downregulated following DHT treatment of T-47D cells. These results were in
agreement with findings from the Human Breast Cancer PCR Array which showed that
the treatments downregulated expression of mesenchymal markers, indicating inhibition
of EMT (Section 4.2.1). In MCF-7 cells, expression of SNAI1 was reduced in
DHT/cyclopamine co-treated MCF-7 cells, however SNAI2 and TWIST1 were
upregulated by DHT and the combination of DHT and cyclopamine treatments (Figure
5.3). SNAI2 and TWIST1 have been characterised previously as AR target genes, and
candidate AREs have been identified in the promoter of the SNAI2 and TWIST1 genes
(Bolton et al 2007, Eide et al 2013). Levels of the epithelial marker, cytokeratin 19
(KRT19), which are reported to be decreased in breast tumours were upregulated in
DHT-treated MCF-7 cells and in DHT and/or cyclopamine treated T-47D cultures
(Figure 5.3, 5.4) (Fuchs et al 2002). These results indicate inhibition or reversal of
EMT.
To investigate the EMT-associated pathways or biological processes that were
potentially enriched, markedly regulated genes (≥1.5-fold) were analysed using the
REACTOME bioinformatics programme (Croft et al 2014). This programme maps the
regulated genes to an existing pathway database and predicts involvement of pathways
according to p-values or significance (ie. low or significant p-values indicate that the
association between genes of interest and pathways is not occurring randomly).
Analysis of data using REACTOME indicated that a similar set of pathways was
regulated in both MCF-7 and T-47D cells and that there were no marked differences in
the types of pathways regulated by DHT, cyclopamine and the combination of DHT and
cyclopamine (Table 5.1, 5.2). In both the MCF-7 and T-47D cells, the most significant
pathway/biological process which had the lowest p-value was extracellular matrix
(ECM) remodelling or organisation (Table 5.1, 5.2). Other pathways regulated in both
the cell lines by DHT and/or cyclopamine included the growth and developmental
pathway, WNT. DHT treatment alone also regulated genes associated with TGFβ
signalling in MCF-7 and T-47D cells, and in MCF-7 cells, cyclopamine and
DHT/cyclopamine co-treatment modulated cell-to-cell communication and BMP
signalling, respectively (Table 5.1, 5.2).
Chapter 5
167
(A)
Efficiency (E): 10-1/slope = 10(-1/-3.3079) = 2.006 %E = (E-1) × 100% = (2.006-1) × 100% = 100.6%
(B)
Efficiency (E): 10-1/slope = 10(-1/-3.4271) = 1.958 %E = (E-1) × 100% = (1.958-1) × 100% = 95.8%
y = -3.3079x + 24.807 R² = 0.9871
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5
Ave
rage
Ct
log cDNA
y = -3.4271x + 19.165 R² = 0.9731
0
2
4
6
8
10
12
14
16
18
0 0.5 1 1.5 2 2.5
Ave
rage
Ct
log cDNA
Chapter 5
168
(C)
Efficiency (E): 10-1/slope = 10(-1/-3.4047) = 1.966 %E = (E-1) × 100% = (1.966-1) × 100% = 96.6%
(D)
Efficiency (E): 10-1/slope = 10(-1/-3.289) = 2.014 %E = (E-1) × 100% = (2.014-1) × 100% = 101.4%
Figure 5.1: Efficiency curves for AR and GAPDH qPCR in (A), (B) MCF-7 and (C), (D) T-47D cells. RNA extracted from MCF-7 or T-47D cells was reverse transcribed and 1:2, 1:10 and 1:20 dilutions of the (100ng) cDNA was prepared for (A), (C) AR and (B), (D) GAPDH qPCR. Experiments were repeated three times and representative results are shown.
y = -3.4047x + 25.52 R² = 0.9984
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5
Ave
rage
Ct
log cDNA
y = -3.2893x + 20.62 R² = 0.9805
02468
101214161820
0 0.5 1 1.5 2 2.5
Ave
rage
Ct
log cDNA
Chapter 5
169
(A)
(B)
Figure 5.2: DHT and cyclopamine regulation of AR mRNA levels. Following treatment of (A) MCF-7 and (B) T-47D cells with 10-8 M DHT and/or 2 μM cyclopamine or 0.1% (v/v) ethanol (vehicle control) for 24 h, RNA was isolated and AR mRNA expression was evaluated by RT-qPCR. AR levels were normalised to corresponding GAPDH levels. Duplicate samples were prepared in each experiment and results are expressed as mean ± S.E.M. of normalised ABCG2 mRNA levels from three independent experiments. Statistical significance relative to controls was calculated using the Mann-Whitney U test, *p<0.05.
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Control DHT Cyclopamine DHT +Cyclopamine
Nor
mal
ised
AR
mR
NA
Lev
els
Treatment (24hrs)
*
Control 10-8 M DHT 2 µM Cyclopamine
10-8 M DHT + 2 µM
Cyclopamine
0
0.2
0.4
0.6
0.8
1
1.2
1.4
Control DHT Cyclopamine DHT +Cyclopamine
Nor
mal
ised
AR
mR
NA
Lev
els
Treatment (24hrs)
*
*
Control 10-8 M DHT 2 µM Cyclopamine
10-8 M DHT + 2 µM
Cyclopamine
Chapter 5
170
(A)
(B)
AHNAK
AKT1
BMP1
BMP2 -3.36
BMP7 -1.58
CALD1 -1.70
CAMK2N1
-13682.08
CAV2
CDH1
CDH2
COL1A2
COL3A1 5.86
COL5A2
CTNNB1
DSC2
DSP 2.95
EGFR
ERBB3
ESR1
F11R
FGFBP1
FN1
FOXC2
FZD7 2.34
GNG11
GSC
GSK3B
IGFBP4
IL1RN
ILK
ITGA5 -2.33
ITGAV
ITGB1
JAG1
KRT14
KRT19 1.59
KRT7 -1.67
MAP1B 2.38
MMP2
MMP3
MMP9 2.22
MSN
MST1R
NODAL
NOTCH1
NUDT13
OCLN
PDGFRB
PLEK2
PPPDE2
PTK2
PTP4A1 1.58
RAC1
RGS2 -1.62
SERPINE1
1.65
SIP1
SMAD2
SNAI1
SNAI2 8.40
SNAI3 -1.67
SOX10
SPARC -1.97
SPP1 -1.47
STAT3
STEAP1
TCF3
TCF4
TFPI2 2.48
TGFB1
TGFB2
TGFB3
TIMP1
TMEFF1
TMEM132A
TSPAN13
TWIST1 1.57
VCAN -1.59
VIM
VPS13A
WNT11
WNT5A
WNT5B 2.20
ZEB1
ZEB2
AHNAK
AKT1
BMP1
BMP2
BMP7
CALD1 -1.94
CAMK2N1
CAV2
CDH1
CDH2
COL1A2
COL3A1 3.42
COL5A2
CTNNB1
DSC2
DSP 2.72
EGFR
ERBB3
ESR1
F11R -1.52
FGFBP1
FN1
FOXC2
FZD7 2.61
GNG11
GSC
GSK3B
IGFBP4
IL1RN
ILK
ITGA5
ITGAV
ITGB1
JAG1
KRT14
KRT19
KRT7 -2.24
MAP1B
MMP2
MMP3
MMP9 2.67
MSN
MST1R
NODAL -2.61
NOTCH1
NUDT13
OCLN
PDGFRB
PLEK2
PPPDE2
PTK2
PTP4A1 1.48
RAC1
RGS2
SERPINE1
1.51
SIP1
SMAD2
SNAI1
SNAI2
SNAI3 -2.24
SOX10
SPARC
SPP1 -1.50
STAT3
STEAP1 1.82
TCF3
TCF4
TFPI2
TGFB1
TGFB2
TGFB3
TIMP1
TMEFF1
TMEM132A
TSPAN13
TWIST1
VCAN -1.54
VIM
VPS13A
WNT11
WNT5A
WNT5B 1.59
ZEB1
ZEB2
Chapter 5
171
(C)
Figure 5.3: DHT and cyclopamine regulation of EMT-associated genes in MCF-7 cells. Genes which were up- or downregulated by ≥1.5-fold in MCF-7 cells treated with (A) 10-8 M DHT, (B) 2 µM cyclopamine and (C) 10-8 M DHT and 2 µM cyclopamine are shown in the EMT PCR array layout with red signals indicating upregulation and green signals indicating downregulation of gene expression. Grey signals are genes which had very low expression or were undetectable in the cells.
AHNAK
AKT1
BMP1
BMP2 -2.51
BMP7
CALD1 -6.30
CAMK2N1
CAV2
CDH1
CDH2
COL1A2
COL3A1 5.29
COL5A2
CTNNB1 -1.62
DSC2 -1.81
DSP 2.87
EGFR
ERBB3
ESR1
F11R
FGFBP1
FN1
FOXC2
FZD7 1.95
GNG11
GSC -1.53
GSK3B
IGFBP4
IL1RN
ILK
ITGA5 -1.82
ITGAV
ITGB1
JAG1
KRT14
KRT19
KRT7
MAP1B 2.35
MMP2
MMP3
MMP9 2.84
MSN
MST1R
NODAL
NOTCH1
NUDT13
OCLN
PDGFRB
PLEK2
PPPDE2
PTK2
PTP4A1 1.53
RAC1
RGS2 2.43
SERPINE1
SIP1
SMAD2
SNAI1 -1.71
SNAI2 5.79
SNAI3
SOX10
SPARC
SPP1
STAT3
STEAP1
TCF3
TCF4
TFPI2 2.12
TGFB1
TGFB2
TGFB3
TIMP1
TMEFF1
TMEM132A
TSPAN13
TWIST1 2.00
VCAN -1.48
VIM
VPS13A
WNT11
WNT5A 1.90
WNT5B 2.06
ZEB1
ZEB2 -1.97
Chapter 5
172
(A)
(B)
AHNAK
AKT1
BMP1
BMP2
BMP7 -2.33
CALD1
CAMK2N1
-4.15
CAV2
CDH1
CDH2 -2.55
COL1A2
COL3A1
COL5A2 -1.72
CTNNB1 -1.54
DSC2 -1.59
DSP -2.30
EGFR
ERBB3 -1.48
ESR1 -1.86
F11R
FGFBP1 -1.47
FN1 -1.67
FOXC2
FZD7 -1.79
GNG11
GSC
GSK3B
IGFBP4 -1.84
IL1RN -2.83
ILK
ITGA5 -5.18
ITGAV
ITGB1
JAG1
KRT14
KRT19 2.77
KRT7 2.07
MAP1B
MMP2
MMP3
MMP9 -2.68
MSN
MST1R -1.71
NODAL -1.54
NOTCH1 -1.69
NUDT13
OCLN -1.73
PDGFRB
PLEK2 -2.61
PPPDE2
PTK2 -1.50
PTP4A1
RAC1
RGS2
SERPINE1
-8.18
SIP1
SMAD2 -1.52
SNAI1 -3.14
SNAI2
SNAI3
SOX10 -4.35
SPARC
SPP1
STAT3
STEAP1 4.72
TCF3
TCF4
TFPI2 -2.91
TGFB1 -4.12
TGFB2
TGFB3 -4.38
TIMP1 -2.22
TMEFF1
TMEM132A
TSPAN13
TWIST1 -2.48
VCAN -4.15
VIM -1.67
VPS13A
WNT11
WNT5A
WNT5B -2.00
ZEB1
ZEB2
AHNAK -1.80
AKT1 -1.60
BMP1 -1.55
BMP2
BMP7
CALD1
CAMK2N1
CAV2
CDH1 -1.48
CDH2
COL1A2 -2.33
COL3A1
COL5A2
CTNNB1 -1.94
DSC2 -1.62
DSP -1.59
EGFR
ERBB3 -1.51
ESR1 -1.46
F11R -1.54
FGFBP1 -2.48
FN1 -1.73
FOXC2
FZD7 -2.11
GNG11
GSC
GSK3B
IGFBP4 -1.94
IL1RN
ILK
ITGA5 -1.79
ITGAV -1.48
ITGB1 -1.47
JAG1 -1.51
KRT14
KRT19 1.80
KRT7 2
MAP1B -2.50
MMP2
MMP3
MMP9 -1.88
MSN
MST1R -1.96
NODAL
NOTCH1 -1.49
NUDT13 -1.58
OCLN -2.83
PDGFRB
PLEK2 -1.78
PPPDE2
PTK2 -1.49
PTP4A1
RAC1
RGS2
SERPINE1
-16.22
SIP1
SMAD2 -1.47
SNAI1 -1.75
SNAI2
SNAI3 -1.73
SOX10 -3.89
SPARC -1.84
SPP1
STAT3
STEAP1
TCF3
TCF4
TFPI2
TGFB1 -2.62
TGFB2
TGFB3
TIMP1 -1.85
TMEFF1
TMEM132A
-1.75
TSPAN13
TWIST1
VCAN
VIM -1.83
VPS13A
WNT11
WNT5A
WNT5B -1.47
ZEB1
ZEB2 -3.51
Chapter 5
173
(C)
Figure 5.4: DHT and cyclopamine regulation of EMT-associated genes in T-47D cells. Genes which were up- or downregulated by ≥1.5-fold in T-47D cells treated with (A) 10-8 M DHT, (B) 2 µM cyclopamine and (C) 10-8 M DHT and 2 µM cyclopamine are shown in the EMT PCR array layout with red signals indicating upregulation and green signals indicating downregulation of gene expression. Grey signals are genes which had very low expression or were undetectable in the cells.
AHNAK
AKT1 -2.31
BMP1
BMP2
BMP7 -2.20
CALD1
CAMK2N1
CAV2
CDH1
CDH2 1.76
COL1A2 -1.50
COL3A1
COL5A2 -1.56
CTNNB1 -1.96
DSC2 -1.71
DSP -2.11
EGFR
ERBB3
ESR1 -1.49
F11R
FGFBP1 -2.22
FN1 -1.68
FOXC2
FZD7 -2.13
GNG11
GSC
GSK3B
IGFBP4 -1.76
IL1RN -4.95
ILK
ITGA5 -2.82
ITGAV
ITGB1 -1.50
JAG1
KRT14
KRT19 3.10
KRT7 2.09
MAP1B
MMP2
MMP3
MMP9 -2.41
MSN
MST1R -1.84
NODAL -1.77
NOTCH1 -1.64
NUDT13
OCLN -1.62
PDGFRB
PLEK2 -2.51
PPPDE2
PTK2
PTP4A1
RAC1
RGS2 -1.92
SERPINE1
-2.02
SIP1
SMAD2
SNAI1 -3.45
SNAI2
SNAI3 -1.62
SOX10 -1.66
SPARC -1.69
SPP1
STAT3
STEAP1 5.40
TCF3
TCF4 -1.59
TFPI2
TGFB1 -3.13
TGFB2
TGFB3 -1.74
TIMP1 -2.14
TMEFF1
TMEM132A
TSPAN13
TWIST1 -2.00
VCAN -2.88
VIM -2.01
VPS13A
WNT11 -1.54
WNT5A
WNT5B
ZEB1
ZEB2
Chapter 5
174
Table 5.1: Pathway enrichment associated with DHT and cyclopamine regulated genes in MCF-7 cells.
Treatment Pathway, p-value
10-8 M DHT
1) Extracellular Matrix (ECM) Organisation (1.84×10-7) ECM Proteoglycans (4.3×10-5) Integrin Cell Surface Interactions (1.66×10-2) Degradation of ECM (3.13×10-2) Fibronectin Matrix Formation (1.6×10-2) Collagen Formation (2.16×10-2) Elastic Fibre Formation (1.61×10-4)
2) WNT Pathway (6.09×10-3)
3) TGFβ Pathway (1.55×10-2)
2 µM Cyclopamine
1) Extracellular Matrix (ECM) Organisation (1.21×10-3) ECM Proteoglycans (8.11×10-3) Integrin Cell Surface Interactions (1.03×10-2) Collagen Formation (1.05×10-2) Degradation of ECM (1.9×10-2)
2) WNT Pathway (1.64×10-3)
3) Cell-Cell Communication (2.57×10-2)
10-8 M DHT + 2 µM
Cyclopamine
1) Extracellular Matrix (ECM) Organisation (3.81×10-4) Elastic Fibre Formation (4.6×10-3) ECM Proteoglycans (1.27×10-2) Integrin Cell Surface Interactions (1.52×10-2) Fibronectin Matrix Formation (1.53×10-2) Collagen Formation (1.99×10-2) Degradation of ECM (2.88×10-2)
2) WNT Pathway (5.16×10-3)
3) BMP Pathway (5.36×10-2)
Genes regulated by ≥1.5-fold were analysed using the REACTOME open-source bioinformatics programme and database, which maps genes to pathways or functional processes. Using this programme, p-values represent the probability of non-random association of the genes of interest overlapping with the pathways. Therefore, the lower the p-value, the less likely that this overlap occurred by chance. Pathways with the lowest p-values are listed as top pathways enriched in the genes. Top three pathways are shown.
Chapter 5
175
Table 5.2: Pathway enrichment associated with DHT and cyclopamine regulated genes in T-47D cells.
Treatment Pathway, p-value
10-8 M DHT
1) Extracellular Matrix (ECM) Organisation (4.39×10-9) Elastic Fibre Formation (2.03×10-7) ECM Proteoglycans (2.26×10-7) Integrin Cell Surface Interactions (1.05×10-4) Non-integrin Membrane-ECM Interaction (3.44×10-4) Degradation of ECM (5.01×10-4) Fibronectin Matrix Formation (8.29×10-4) Collagen Formation (1.66×10-2)
2) TGFβ Pathway (6.01×10-6)
3) WNT Pathway (3.11×10-2)
2 µM Cyclopamine
1) Extracellular Matrix (ECM) Organisation (3.87×10-10) ECM Proteoglycans (4.15×10-10) Elastic Fibre Formation (5.4×10-6) Integrin Cell Surface Interactions (7.34×10-6) Fibronectin Matrix Formation (8.29×10-6) Non-integrin Membrane-ECM Interaction (2.08×10-5) Degradation of ECM (5×10-5) Collagen Formation (2.05×10-3)
2) TGFβ Pathway (6.01×10-6)
3) WNT Pathway (3.11×10-2)
10-8 M DHT + 2 µM
Cyclopamine
1) Extracellular Matrix (ECM) Organisation (5.6×10-9) ECM Proteoglycans (4.93×10-10) Elastic Fibre Formation (2.27×10-7) Fibronectin Matrix Formation (8.76×10-6) Non-integrin Membrane-ECM Interaction (2.28×10-5) Integrin Cell Surface Interactions (1.15×10-4) Degradation of ECM (5.46×10-4) Collagen Formation (1.74×10-2)
2) TGFβ Pathway (9.71×10-5)
3) WNT Pathway (8.88×10-3)
Genes regulated by ≥1.5-fold were analysed using the REACTOME open-source bioinformatics programme and database, which maps genes to pathways or functional processes. Using this programme, p-values represent the probability of non-random association of the genes of interest overlapping with the pathways. Therefore, the lower the p-value, the less likely that this overlap occurred by chance. Pathways with the lowest p-values are listed as top pathways enriched in the genes. Top three pathways are shown.
Chapter 5
176
5.2.1.1 Effects of DHT and Cyclopamine on ECM Remodelling
During EMT, the ECM remodels following increased deposition and cross-linking of
fibrillar collagens in the ECM, and increased cell-to-ECM interactions/adhesions such
as the binding of cell surface receptors (e.g. integrins) to ECM components (e.g.
collagen, fibronectin, vitronectin) (Bonnans et al 2014). This facilitates cell migration
and invasion. Degradation of ECM components by enzymes, including matrix
metalloproteinases (MMPs) also facilitates cell movement and invasion into the ECM
via cleavage of ECM components to create tracks for migration (Bigg et al 2007, Wolf
et al 2013). In MCF-7 cells, DHT downregulated the mRNA levels of ECM
components, SPARC and versican (VCAN), although DHT treatment or
DHT/cyclopamine co-treatment also upregulated expression of collagen 3 alpha 1
(COL3A1) (Figure 5.5). In contrast to MCF-7 cells, DHT and cyclopamine treatments
predominantly downregulated expression of genes encoding ECM components in T-
47D cells, including the collagens, COL5A2, fibronectin (FN1) and SPARC, indicating
inhibition of cell-ECM interactions. SERPINE1 encodes plasminogen activator inhibitor
1 (PAI-1), and its increased expression is associated with EMT (Zavadil et al 2004,
Labelle et al 2011). Although SERPINE1 mRNA levels were upregulated by 1.5 and 1.6
fold in MCF-7 cells treated individually with DHT or cyclopamine, respectively, the
combination of DHT and cyclopamine treatments led to a smaller upregulation of
SERPINE1 levels. In contrast, SERPINE1 expression was markedly downregulated in
DHT and/or cyclopamine treated T-47D cells (Figure 5.5).
Formation of integrin- and fibronectin-mediated cell-to-ECM interactions on the cell
surface allows connection between cells and the ECM to induce re-organisation of the
intracellular actin cytoskeleton and initiation of cell movement (Bonnans et al 2014).
mRNA levels of integrin alpha 5 (ITGA5) were suppressed following DHT and
cyclopamine treatments in both MCF-7 and T-47D cells (Figure 5.5). According to the
KEGG database, interactions between the ECM components (e.g. collagens,
fibronectin) and integrins lead to remodelling of the actin cytoskeleton, formation of
cell edge protrusions (filopodia and lamellipodia) and cell motility. As such,
downregulation of expression of the ECM components and ITGA5 would impede
movement of MCF-7 and T-47D cells (Figure 5.6, 5.7). In T-47D cells, expression of
integrin beta 1 (ITGB1) was also downregulated which suggests that binding of
fibronectin to integrins in the cells is suppressed. Proteins encoded by ITGA5 and
ITGB1 along with the collagens and TGFB1, which were markedly downregulated
Chapter 5
177
following DHT and cyclopamine treatments of T-47D cells are also involved in non-
integrin membrane-ECM interactions. Expression of the bone morphogenetic proteins
(BMPs) encoded by BMP1, BMP2 or BMP7 was decreased following DHT and
cyclopamine treatments of MCF-7 and T-47D cells (Figure 5.5). BMPs are extracellular
growth factor proteins belonging to the TGFβ superfamily that can be sequestered in
elastic fibres in the ECM, blocking BMP from reaching its cellular receptors for
activation of BMP-mediated signalling which regulates cell proliferation, differentiation
and migration (Alarmo and Kallioniemi 2010). BMP-1 has been reported to interact
with fibronectin in the ECM and induce cross-linking of collagens, facilitating cell
migration and invasion (Maruhashi et al 2010). In breast cancer cell lines, MCF-7 and
MDA-MB-231, overexpression of BMP2 and BMP7 have also been shown to increase
the migration and invasion of cells (Clement et al 2005, Alarmo et al 2009). Therefore,
downregulation of expression of the BMP genes may indicate inhibition of cell motility
and invasiveness.
Expression of regulators of ECM degradation was also modulated by DHT and
cyclopamine treatments. MMP9 expression was upregulated by 2 to 3 fold following
treatment of MCF-7 cells with DHT, cyclopamine or the combination of DHT and
cyclopamine (Figure 5.3, 5.5). In contrast, in T-47D cells, expression of both MMP9
and tissue inhibitor of metalloproteinases, TIMP1 were markedly downregulated
following DHT and/or cyclopamine treatments (Figure 5.3, 5.5). TIMP1 exhibits dual
EMT-associated functions, inhibiting the proteolytic effects of MMPs and ECM
degradation, but also able to promote EMT via inducing the expression of TWIST1
(D'Angelo et al 2014).
5.2.1.2 DHT and Cyclopamine Regulation of the WNT and TGFβ Pathways
Overexpression of intermediates of pro-EMT signalling pathways such as WNT and
TGFβ increases expression of EMT transcription factors (e.g. SNAI1, TWIST1) and
molecules which lead to re-organisation of the actin cytoskeleton, cell-to-ECM
interactions, migration and invasion (Talbot et al 2012). Genes associated with WNT
signalling (WNT5B, FZD7, CTNNB1, TCF4) were differentially expressed in MCF-7
and T-47D cells following DHT and cyclopamine treatments. In MCF-7 cells, WNT5A
and WNT5B, which encode the non-canonical WNT5A and WNT5B ligands,
respectively, in the planar cell polarity (PCP) pathway, and the Frizzled receptor, FZD7
Chapter 5
178
were markedly upregulated by DHT and/or cyclopamine, suggesting that actin
cytoskeleton remodelling is activated (Figure 5.3, 5.5, 5.6). Despite this, β-catenin
(CTNNB1), a downstream effector of the canonical WNT signalling pathway which
facilitates TCF/LEF-mediated activation of the transcription of WNT target genes, was
found to be markedly downregulated following co-treatment with DHT and
cyclopamine (Figure 5.3, 5.5, 5.6). Decreased expression of CTNNB1 indicates
inhibition of canonical WNT signalling and potentially inhibition of WNT-induced
EMT as WNT/β-catenin target genes include the EMT transcription factors, TWIST1
and SLUG (Borchers et al 2001, Vallin et al 2001). In T-47D cells, DHT and
cyclopamine treatments markedly reduced expression of the WNT-associated genes,
WNT5B, FZD7, CTNNB1 as well as TCF4, which is a major effector of canonical WNT
signalling (Faro et al 2009). These results indicate that the treatments inhibit both
canonical and non-canonical WNT pathways in T-47D cells via downregulation of
WNT/β-catenin effectors and WNT5B and FZD7 in the PCP pathway (Figure 5.4, 5.5,
5.7).
Regulators of the TGFβ signalling pathway were also downregulated in T-47D cells
treated with DHT and/or cyclopamine (Figure 5.4 and 5.7). As TGFβ signalling induces
EMT and EMT-associated cell migration and invasion in cancer cells via upregulation
of EMT transcription factors, reduced expression of TGFB1 which encodes the TGF-β1
ligand and the pathway effector and transcription factor, SMAD2, indicate that the
transcriptional regulatory activity of the pathway was reduced (Xu et al 2009). In
support of this result, expression of SERPINE1, which has been shown to be a target of
TGFβ signalling, was also downregulated (Figure 5.4, 5.5) (Zavadil et al 2004, Labelle
et al 2011).
5.2.1.3 Classification of DHT and Cyclopamine-Specific Pathways
To identify pathways that are specific to DHT or cyclopamine treatments, three-wheeled
Venn diagrams were constructed (Figure 5.8). In MCF-7 and T-47D cells, treatments
with DHT, cyclopamine and the combination of DHT and cyclopamine regulated
expression of genes involved in EMT-associated processes or components including the
ECM proteoglycans (SPARC, COL3A1, COL1A2, VCAN, COL5A2), integrin cell
surface interactions (ITGA5, COL3A1, ITGB1, COL1A2, COL5A2), degradation of the
ECM (MMP9) and WNT signalling pathway (CTNNB1, AKT1, TCF4, FZD7) (Figure
Chapter 5
179
(A)
WNT Pathway
Programmed Cell Death
TGFβ Pathway
Non-Integrin Membrane-ECM
Interaction
Elastic Fibre Formation
Fibronectin Matrix Formation
Degradation of ECM
Integrin Cell Surface Interaction
ECM Proteoglycans
Collagen Formation
Extracellular Matrix (ECM) Organisation
COL1A2
TGFB3 VCAN SERPINE1 FN1
SPARC
ITGB1
TGFB1 COL1A2 COL5A2 ITGA5
COL5A2
F11R
ITGB1 FN1
FN1 BMP1 COL1A2
COL5A2
TIMP1 MMP9
ITGB1 FN1 ITGA5
TGFB1
ITGB1 FN1
ITGA5 BMP7 TGFB3
BMP1
MMP9 COL5A2
COL1A2
ITGB1 FN1
COL1A2 TGFB1 COL5A2
OCLN
DSP PTK2 CTNNB1 VIM
AKT1
SMAD2
F11R SERPINE1 WNT5B TCF4
TGFB1
AKT1
FZD7 CTNNB1
Chapter 5
180
(B)
Figure 5.5: Classification of DHT and cyclopamine regulated EMT-associated genes in MCF-7 and T-47D cells. Heatmaps indicate genes regulated by ≥1.5-fold and classified into pathways or processes using the REACTOME bioinformatics programme in (A) T-47D and (B) MCF-7 cells.
Magnitude of log2 (Fold Change)
0 -2.432 2.432
COL3A1
SPARC VCAN COL3A1 ITGA5
SERPINE1
COL3A1
ITGA5 ITGA5 BMP2 BMP7
MMP9
SERPINE1
FZD7 CTNNB1
Extracellular Matrix (ECM) Organisation
WNT Pathway
Programmed Cell Death
DSP CTNNB1 WNT5B
TGFβ Pathway
Elastic Fibre Formation
Fibronectin Matrix Formation Degradation of ECM
Integrin Cell Surface Interaction
ECM Proteoglycans
WNT5A
(A)
(B)
VCAN
SPAR
C
CO
L3A1
IT
GA5
SNA
IL1
SNA
IL2
TWIS
T1
EMT
FZD
7 C
TNN
B1
181
(C)
Figu
re 5
.6: M
appi
ng o
f D
HT
and
cycl
opam
ine
regu
late
d EM
T-as
soci
ated
gen
es in
MC
F-7
cells
to c
anon
ical
pat
hway
s. U
sing
the
KEG
G p
athw
ay
data
base
, gen
es re
gula
ted
by ≥
1.5-
fold
and
ana
lyse
d by
REA
CTO
ME
wer
e m
appe
d to
the
top
path
way
s en
riche
d in
the
gene
s, (A
) ext
race
llula
r mat
rix
(EC
M)-
rece
ptor
inte
grin
cel
l sur
face
inte
ract
ions
, (B
) ca
noni
cal W
NT
sign
allin
g an
d (C
) no
n-ca
noni
cal W
NT
path
way
or
plan
ar c
ell p
olar
ity (
PCP)
pa
thw
ay. G
enes
show
n to
be
up- o
r dow
nreg
ulat
ed in
the
PCR
arr
ays a
re in
dica
ted
in re
d an
d gr
een,
resp
ectiv
ely.
WN
T
WN
T5B
FZD
7
WN
T5A
182
(A)
(B)
VCAN
CO
L5A2
ITG
A5
ITG
B1
FN1
SERP
INE1
TGFB
1 SM
AD2
183
(C)
(D)
Figu
re 5
.7: M
appi
ng o
f D
HT
and
cycl
opam
ine
regu
late
d EM
T-as
soci
ated
gen
es in
T-4
7D c
ells
to
cano
nica
l pat
hway
s. U
sing
the
KEG
G p
athw
ay
data
base
, gen
es re
gula
ted
by ≥
1.5-
fold
and
ana
lyse
d by
REA
CTO
ME
wer
e m
appe
d to
the
top
path
way
s en
riche
d in
the
gene
s, (A
) ext
race
llula
r mat
rix
(EC
M)-
rece
ptor
and
inte
grin
cel
l sur
face
inte
ract
ions
, (B
) TG
Fβ p
athw
ay, (
C)
cano
nica
l WN
T si
gnal
ling
and
(D)
non-
cano
nica
l WN
T pa
thw
ay o
r pl
anar
cel
l pol
arity
(PC
P) p
athw
ay. G
enes
show
n to
be
up- o
r dow
nreg
ulat
ed in
the
PCR
arr
ays a
re in
dica
ted
in re
d an
d gr
een,
resp
ectiv
ely.
SNA
IL1
SLU
G
TWIS
T1
EMT
FZD
7 C
TNN
B1
WN
T
WN
T5B
FZD
7
184
Chapter 5
185
(A)
(B)
Figure 5.8: Pathways associated with genes regulated by ≥1.5-fold following DHT and cyclopamine treatments of (A) MCF-7 and (B) T-47D cells.
DHT Cyclopamine
DHT + Cyclopamine
TGFβ Pathway
Integrin Cell
Surface Interaction
Elastic Fibre Formation
ECM Proteoglycans
Degradation of ECM
WNT Pathway
MCF-7
DHT Cyclopamine
DHT + Cyclopamine
Collagen Formation
WNT Pathway
TGFβ Pathway
T-47D
ECM Proteoglycans
Integrin Cell Surface
Interaction
Degradation of ECM
Fibronectin Matrix
Formation Elastic Fibre Formation
Fibronectin Matrix
Formation
Chapter 5
186
5.5, 5.8). Additionally, in T-47D cells, DHT and/or cyclopamine treatments also
regulated genes which encode components of TGFβ signalling (TGFB1, SERPINE1,
F11R) and formation of the fibronectin matrix (ITGA5, ITGB1, FN1) and elastic fibres
(BMP7, TGFB3, TGFB1, ITGA5, ITGB1). DHT-treated and DHT and cyclopamine co-
treated MCF-7 cultures exhibited downregulated expression of genes associated with
fibronectin matrix (ITGA5) and elastic fibre (BMP2) formation, while collagen
formation (MMP9, COL5A2) was regulated in T-47D cells (Figure 5.5, 5.8).
5.2.2 DHT and Cyclopamine Effects on MCF-7 Cell Migration and Invasion
Results from analysis of the EMT PCR Arrays indicated that DHT and cyclopamine
may inhibit or mediate the reversal of EMT in breast cancer cells as the treatments
predominantly downregulated expression of genes which encode intermediates of the
pro-EMT, WNT and TGFβ signalling pathways, factors mediating interaction between
cells and the ECM and EMT mesenchymal markers. Further investigation of the EMT
PCR Array findings by validation of mRNA and protein expression of the DHT and
cyclopamine regulated genes was not able to be carried out due to time constraints but
may be performed in future studies. As cancer-associated EMT promotes cell migration
and invasion, inhibition of these processes would support findings from the PCR arrays
that EMT is being inhibited or reversed. Therefore, to investigate DHT and cyclopamine
regulation of cell migration and invasion, in vitro scratch wound healing assays were
performed to evaluate cell migration, and BioCoat™ Matrigel™ Invasion Chamber and
3D Matrigel™ colony formation assays were used to investigate cell invasion.
The migration of DHT and/or cyclopamine treated MCF-7 cells into a wound area
created by scratching confluent monolayer cultures was determined by measuring the
percentage of wound closure after 72 h. Prior to the generation of the ‘wound’, cells
were pre-treated with 10-8 M DHT and/or 2 µM cyclopamine for 4 days (Section
3.1.5.6). In control (0.1% (v/v) ethanol)-treated MCF-7 cultures, 75±5.19% of the
wounds were repopulated with cells at 72 h (Figure 5.9). In contrast, in cyclopamine-
treated cells, wound closure was decreased to 57.7±1.02% at 72 h, while in DHT-treated
and DHT/cyclopamine co-treated cells, wound closure of only 29.0±1.48% and
36.3±1.86%, respectively, was evident at 72 h (Figure 5.9). The decreased wound
closure in the treated cells was evident at 24 h post wound generation and persisted for
the duration of the treatment periods (Figure 5.9).
Chapter 5
187
To investigate DHT and cyclopamine effects on MCF-7 cell invasion, BioCoat™
Matrigel™ Invasion Chamber assays were initially used. For these assays, MCF-7 cells
were seeded into the upper chamber of BioCoat™ Matrigel™ Invasion Chambers and the
numbers of cells that had migrated into the lower chamber by invasion and migration
through the Matrigel™ layer were calculated (Section 3.1.5.7). When MCF-7 cells were
initially seeded at 5×104 cells per well as reported previously (Girnita et al 2012, Park et
al 2013), only ~20 cells had invaded into the lower chamber at 24 h (data not shown).
The seeding densities of MCF-7 cells were therefore increased (1×105 and 2×105 cells
per chamber) and cultures were incubated for longer periods (up to 48 h), however the
numbers of cells invading into the lower chamber remained at 20-39 cells (data not
shown). As the low numbers of cells invading through the Matrigel™ would not permit
detection of inhibition of invasion by the treatments, use of this method was ceased.
In order to investigate cell invasion, an alternative Matrigel™-based method, the 3D
Matrigel™ colony formation assay was performed. This assay has been used previously
to study the morphologies of normal and malignant epithelial cells in three-dimensional
cultures and to investigate the extent of cancer cell invasion into Matrigel™ (Debnath et
al 2003, Lee et al 2007, Quail et al 2012). For this assay, MCF-7 cells were cultured in
Matrigel™ containing 10-8M DHT, 2µM cyclopamine or the combination of 10-8M DHT
and 2 µM cyclopamine for 10 days (Section 3.1.5.8). Images of colonies formed in the
Matrigel™ were quantitated using Image J to estimate colony size (pixels), which
represents the ability of colonies to invade into the surrounding Matrigel™. In
comparison to control (0.1% (v/v) ethanol)-treated MCF-7 cultures (100%),
cyclopamine treatment of MCF-7 cells decreased the median colony size to
87.2±11.81% (which did not reach significance), and following DHT and the
combination of DHT and cyclopamine treatments, the median colony sizes were
significantly decreased to 58.1±1.46% and 62.9±5.21% of controls, respectively (Figure
5.10). Formation of smaller colonies in DHT and/or cyclopamine treated cultures
indicated inhibition of invasion of MCF-7 colonies into Matrigel™.
Chapter 5
188
Figure 5.9: DHT and cyclopamine effects on MCF-7 cell migration. MCF-7 cells were pre-treated for 4 days with 10-8 M DHT, 2 µM cyclopamine or the combination of 10-8
M DHT and 2 µM cyclopamine prior to generation of wound areas between the confluent cells. Images of the wound areas were captured every 24 h post scratching of the cell monolayer and the percentages of wound closure relative to values at time 0 were calculated using TScratch 1.0. Experiments were repeated three times and representative results (mean ± S.E.M.) are shown. Statistical significance relative to vehicle controls (0.1% (v/v) EtOH) was calculated using the Mann-Whitney U test, *p<0.05.
0
10
20
30
40
50
60
70
80
90
0 24 48 72
Wou
nd c
losu
re (%
)
Time (hours)
Ethanol control
DHT
Cyclopamine
DHT + Cyclopamine
0h
24h
48h
72h
Control 10-8 M DHT
10-8 M DHT + 2 µM
Cyclopamine 2 µM
Cyclopamine
*
*
*
Vehicle (0.1% (v/v) EtOH) DHT Cyclopamine
DHT + Cyclopamine
Chapter 5
189
0 10000 20000 30000 40000 500000
10
20
Colony size (pixels)
Col
onie
s
0 10000 20000 30000 40000 500000
10
20
Colony size (pixels)
Col
onie
s
0 10000 20000 30000 40000 500000
10
20
Colony size (pixels)
Col
onie
s
0 10000 20000 30000 40000 500000
10
20
Colony size (pixels)
Col
onie
s
(A)
Control 10-8 M DHT
2 µM Cyclopamine 10-8 M DHT +
2 µM Cyclopamine
Chapter 5
190
0
20
40
60
80
100
120
Med
ian
Num
ber
of P
ixel
s (%
)
Treatment
(B)
Figure 5.10: DHT and cyclopamine regulation of MCF-7 cell invasion. MCF-7 cells were cultured for 10 days in Matrigel containing 10-8 M DHT and/or 2 μM cyclopamine. (A) Number of colonies and colony size (pixels) were quantitated using Image J, with representative images (day 10) shown. (B) Median colony size (pixels) is depicted for each of the treatment groups. Experiments, performed in triplicate wells, were repeated three times. Representative results of the average of median pixels ± S.E.M. from the triplicate wells are shown. Statistical significance was calculated relative to results from vehicle (0.1% (v/v) ethanol) treated cultures by Mann-Whitney U test, *p<0.05.
Control (0.1% (v/v)
EtOH)
10-8 M DHT
2 µM Cyclopamine
10-8 M DHT + 2 µM
Cyclopamine
* *
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5.3 Discussion
The transition from an epithelial to a mesenchymal phenotype of cancer cells (EMT) is
associated with tumour invasion and metastasis. Hallmarks of EMT include elevated
expression of the mesenchymal markers, vimentin and N-cadherin, increased levels of
transcription factors, SNAI1, SLUG, TWIST1, and a concomitant decrease in
expression of epithelial markers such as the cytokeratins. The EMT programme is
induced by a number of signalling pathways, notably the TGFβ, WNT and NOTCH
pathways, and involves a series of events that promote cell migration and invasion,
including dissociation of cell-to-cell adhesion, formation of focal adhesions or cell-to-
ECM adhesions mediated by integrins, collagens and fibronectin, and proteolytic
cleavage of the ECM (Yilmaz and Christofori 2009, Tsai and Yang 2013). In this study,
preliminary findings from investigation of DHT- and cyclopamine-induced regulation
of expression of breast cancer-associated genes in MCF-7 and T-47D cells using RT2
Profiler Human Breast Cancer PCR Arrays (Section 4.2.1) indicated that the treatments
reduced expression of TGFβ1, SRC, NOTCH1 and TWIST1, suggesting inhibition or
reversal of EMT.
A more specific examination of DHT and cyclopamine effects on EMT using Human
EMT PCR Arrays identified that in addition to downregulation of the expression of
mesenchymal markers and upregulation of epithelial marker expression, genes whose
encoded products mediate other EMT-associated processes and pathways were also
downregulated. These processes included remodelling of the ECM (VCAN, SPARC,
collagens, integrins (ITGA5 and ITGB1)), ECM degradation (MMP9), TGFβ signalling
(TGFB1, SMAD2, SERPINE1), and WNT signalling (FZD7, WNT5B). Similar findings
have been reported in previous studies using cell lines of other cancer types. For
example, in the LNCaP prostate cancer cell line, high-throughput screening of androgen
regulated genes also identified a number of EMT-associated genes regulated by the
synthetic androgen, R1881. These genes encoded proteins involved in cell-to-cell or
cell-to-ECM interactions (e.g. integrin alpha V (ITGAV), laminin α4, fibronectin (FN1),
occludin), TGFβ signalling (SERPINE1) and WNT signalling (FZD3) (DePrimo et al
2002). Treatment of ovarian cancer cells with 3-keto-N-(aminoethyl-aminocaproyl-
dihydrocinnamoyl)-cyclopamine also downregulated levels of mRNAs encoding
membrane type 1 matrix metalloproteinase (MT1-MMP) and β1 integrin, both of which
induce remodelling of the ECM during EMT (Liao et al 2009).
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Pathway enrichment analysis of the EMT arrays identified that DHT and/or
cyclopamine treatments reduced expression of genes associated with the TGFβ
signalling pathway; TGFB1, SMAD2 and SERPINE1 in T-47D cells. As SERPINE1 is a
TGFβ signalling-induced target gene, the PCR array results indicated that DHT and
cyclopamine inhibited TGFβ-mediated gene transcription (Xu and Kapoun 2009).
SERPINE1 has also been shown to be upregulated in cancer-associated EMT, and
therefore its downregulation suggests reversal of EMT (Zavadil et al 2001, Xu and
Kapoun 2009, Labelle et al 2011). Of interest, reciprocal regulation of the AR or
Hedgehog signalling pathways and the TGFβ pathway has been reported in a number of
cancer cell lines (Kang et al 2001, Steinway et al 2014). Direct interaction between
SMAD3 and the AR were demonstrated in the SW480.7 colon carcinoma cell line and
overexpression of both SMAD3 and AR in the cells enhanced AR-mediated
transactivation, thereby suggesting that SMAD3 could function as a co-activator of AR
transcriptional activity (Kang et al 2001). TGF-β1 treatment of the human
hepatocellular carcinoma cell line, PLC/PRF/5, which stimulated EMT by increasing
expression of N-cadherin and decreasing expression of E-cadherin, also upregulated
GLI2 mRNA and protein expression, suggesting that the Hedgehog pathway may be
involved in mediating TGFβ-induced EMT in hepatocellular carcinoma (Steinway et al
2014). In addition to findings from the present study showing DHT and cyclopamine
induced downregulation of the expression of genes associated with the TGFβ pathway,
it is possible that decreased TGFβ pathway activity reciprocally regulates AR and
Hedgehog signalling, with these interactions potentially important in the manifestation
or modulation of EMT.
Elevated expression of WNT ligands, FZD receptors and the TCF/LEF transcription
factors, and increased nuclear levels of β-catenin in the canonical WNT/β-catenin
signalling pathway are associated with progression of EMT (Wu et al 2012a,
MacMillan et al 2014). DHT and cyclopamine treatments downregulated mRNA levels
of the β-catenin gene, CTNNB1, in MCF-7 cells, and CTNNB1, TCF4, WNT5B and
FZD7 in T-47D cells, with co-treatment of the cells with DHT and cyclopamine
enhancing DHT- or cyclopamine-induced downregulation of CTNNB1 in MCF-7 cells
and TCF4 in T-47D cells. These results indicated inhibition of canonical WNT
signalling, and supporting this hypothesis, AKT1, a target gene of WNT signalling, was
shown in the EMT arrays to be repressed in DHT and cyclopamine co-treated T-47D
cells (Wang et al 2011b). An interesting finding from the EMT PCR arrays was that
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WNT5B levels were downregulated in T-47D cells, which was consistent with decreased
WNT signalling and inhibition of EMT, but WNT5A and WNT5B levels were
upregulated in DHT and/or cyclopamine treated MCF-7 cells. E2 treatment of T-47D
cells has been shown to increase WNT5B mRNA levels (Saitoh and Katoh 2002), while
treatment of MCF-7 cells with recombinant WNT5B was reported to increase cell
invasion, a result that is consistent with both induction of WNT signalling and
promotion of EMT. Regulation of WNT5A and WNT5B mRNA and protein levels by
DHT and cyclopamine treatments should be validated in future studies incorporating
longer timepoints and utilising anti-androgens and Hedgehog pathway ligands to
confirm results in MCF-7, T-47D and other breast cancer cell lines. Although
upregulated WNT5A and WNT5B expression in MCF-7 cells suggests induction of WNT
signalling, which would promote EMT, the marked downregulation of CTNNB1 that
encodes the WNT signalling effector β-catenin indicates decreased WNT signalling and
therefore, inhibition of EMT, a hypothesis that is more consistent with results of
migration and invasion assays.
Interactions between integrin heterodimers (αvβ3, α6β1, α6β4, α5β1 and α1β1) and
components of the ECM (e.g. collagens, laminin, fibronectin) facilitate cell migration
(Bonnans et al 2014). In MCF-7 cells, elevated expression of α5β1 integrin has been
associated with increased cell invasion (Morozevich et al 2009). In the present study,
DHT and cyclopamine treatments of MCF-7 cells downregulated expression of ITGA5,
which encodes α5 integrin while in T-47D cells, ITGA5 and ITGB1, which encodes β1
integrin were downregulated. α5 integrin is a major partner of the β1 integrin subunit
(Goel et al 2010). Therefore, downregulation of α5 and/or β1 integrin suggests
inhibition of the formation of α5β1 integrins and suppression of cell migration and
invasion. Fibronectin in the ECM is a ligand which binds to α5β1 integrins to induce
cell migration (Jia et al 2004). In the EMT PCR array, the gene encoding fibronectin,
FNI, was also downregulated in T-47D cells following DHT and cyclopamine
treatments, further supporting inhibition of integrin α5β1-fibronectin interaction and cell
invasion mediated by integrin α5β1 heterodimers. Hormones other than androgens have
been shown to modulate expression of integrins, for example, E2 induces elevation of
integrin α5, α6 and β1 mRNA levels in endothelial cells (Cid et al 1999). The E2-
stimulated increase in ITGA5 expression in MCF-7 cells has been shown to be mediated
via formation of ERα/Sp1 complexes which bind to an Sp1 binding site located in the
ITGA5 promoter (Sisci et al 2010). Since androgens inhibit oestrogen/ER-mediated
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effects, it is possible that DHT-induced downregulation of α5 and β1 integrins observed
in this study may be mediated in part via inhibition of ER signalling (Peters et al 2009,
Need et al 2012).
Genes encoding type I and V collagens, COL1A2 and COL5A2, respectively, were
markedly downregulated in T-47D cells treated with DHT and/or cyclopamine whereas
in MCF-7 cells, the type III collagen, COL3A1 was upregulated. Collagens interact with
receptors on the cell surface (e.g. integrins) to initiate cell migration, and elevated
synthesis and deposition of collagens in the ECM induce cross-linking of the ECM
which contributes to cell invasion (Provenzano et al 2006). In vivo, deposition of type I
and III collagen bundles was shown to be localised at the invasive front of infiltrating
breast ductal carcinomas, indicating the role of collagens in facilitating tumour invasion
(Kauppila et al 1998). Therefore, downregulation of COL5A2 and COL1A2 in T-47D
cells suggests reversal of cell invasiveness. In contrast, levels of COL3A1 were
upregulated following DHT treatment of MCF-7 cells, a similar finding to previously
reported upregulation of Col3a1 in DHT-treated murine skeletal muscle tissue
(Svensson et al 2010). Matrix metalloproteinases (MMPs) contribute to cell invasion
but are also capable of controlling the aberrant overproduction of collagens by cleaving
and inactivating collagens as well as other ECM components. For example, MMP2 and
MMP9 have been shown to cleave type I and III collagens (Bigg et al 2007). In MCF-7
cells, MMP9 expression was markedly upregulated following DHT and/or cyclopamine
treatments, and it is possible that DHT-induced increases in COL3A1 expression may be
counteracted by secretion of MMP9 enzymes.
Upregulation of mesenchymal markers and downregulation of epithelial markers are
characteristics of EMT. DHT and/or cyclopamine treatments of MCF-7 and T-47D cells
markedly downregulated expression of the EMT-inducing transcription factor, SNAI1 in
MCF-7 and T-47D cells as well as the EMT mesenchymal markers, VIM and N-
cadherin (CDH2) in T-47D cells. The epithelial marker, cytokeratin-19 (KRT19) was
also upregulated in both cell lines in response to DHT and cyclopamine treatments.
These results are in agreement with an earlier study which showed that ectopic
expression of GLI1 in mammary gland of mouse models, which led to formation of
breast tumours, was associated with EMT progression, with expression of E-cadherin
downregulated and SNAI1 upregulated in the tumours (Fiaschi et al 2009). However,
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others have reported that DHT stimulates EMT in MCF-7 and T-47D cells by
transcriptionally downregulating the expression of E-cadherin, results that are
contradictory to those observed in this thesis study (Liu et al 2008, Zhu and Kyprianou
2010). Androgens have been reported previously to exhibit divergent effects in
individual breast cancer cell lines, in particular the MCF-7 cell line, in which androgens
are documented to be either inhibitory or to stimulate proliferation (Birrell et al 1995,
Szelei et al 1997, Greeve et al 2004, Macedo et al 2006, Cops et al 2008). While
differences in the androgen responsiveness of breast cancer cell lines may in part be due
variation between isolates of the cell lines and use of cell lines that have undergone
extensive passaging, potentially altering the ratio of AR to ER expression in the cells,
reasons for these well-documented discrepancies are generally unknown. However, the
previously successful treatment of breast cancers with androgens (Section 1.4.4.4) and
the fact that MCF-7 cells have been classified as luminal A (Section 1.2.1) are
consistent with an inhibition of EMT following DHT treatment.
Although comprehensive validation and investigation of the EMT PCR Array results are
important future directions of this work, downregulation of the expression of EMT-
associated genes following DHT and/or cyclopamine treatments of MCF-7 and T-47D
cells suggested that the treatments reverse EMT. The abilities of cancer cells to migrate
and invade into the surrounding tumour microenvironment are promoted by EMT,
therefore DHT and cyclopamine treatments were hypothesised to inhibit the migration
and invasion of breast cancer cells. In support of this hypothesis, inhibition of MCF-7
cell migration following DHT, cyclopamine and DHT/cyclopamine treatments was
shown using wound healing assays in the present study. In contrast to these results,
others have reported stimulation of MCF-7 cell migration by DHT, which was
associated with DHT-induced activation of EMT (Liu et al 2008, Zhu and Kyprianou
2010). Androgens, DHT and R1881, have been shown to increase LNCaP prostate
cancer cell migration and to also downregulate expression of E-cadherin and re-organise
the actin cytoskeleton, which are indicative of an induction of EMT (Liao et al 2003,
Zhu and Kyprianou 2010). Inhibition of MCF-7 cell migration following cyclopamine
treatment is in agreement with previous studies where knockdown of GLI1 in MCF-7
cells was shown to abrogate cell migration (Sun et al 2014). However, in a study by
Sabol et al, cyclopamine-mediated downregulation of MCF-7 cell migration, which was
investigated using wound healing assays, was not significant, possibly because wound
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closure was measured at 26 h while in this study, cyclopamine was found to markedly
inhibit MCF-7 cell migration at later timepoints (up to 72 h) (Sabol et al 2014).
DHT and DHT/cyclopamine treatments were also shown to inhibit MCF-7 cell invasion
using 3D Matrigel™ colony formation assays. Initial studies of MCF-7 cell invasion
were unsuccessful using the BioCoat™ Matrigel™ Invasion Chambers likely due to the
poor invasive abilities of MCF-7 cells (McSherry et al 2011). In other studies where
MCF-7 cell invasion was investigated, BioCoat™ Matrigel™ Invasion Chambers were
similarly not used, while in most studies which reported usage of these chambers,
stimulation of MCF-7 cell invasion was being evaluated (Wicki et al 2006, Rosman et
al 2008, Walsh et al 2010, McSherry et al 2011, Yang and Kim 2014). As the invasion
chamber assays were unsuitable in this study, an alternative 3D Matrigel™ colony
formation assay, which has been used to investigate cancer cell invasion, was performed
(Debnath et al 2003, Lee et al 2007, Quail et al 2012). Androgen regulation of MCF-7
cell invasion has not been investigated previously, however in the prostate cancer cell
lines, LNCaP and MDA PCa 2b, DHT treatment or overexpression of the AR has been
shown to increase cell invasion (Hara et al 2008, Li et al 2009, Zhu and Kyprianou
2010). In this study, cyclopamine treatment alone did not significantly alter MCF-7 cell
invasion into Matrigel™, a result that is in contrast to previous reports which found
inhibition of MCF-7 cell invasion following knockdown of GLI1 or treatment with
cyclopamine (Che et al 2013, Sun et al 2014). However, in those studies, cell invasion
was investigated using BioCoat™ Matrigel™ Invasion Chambers and the MCF-7 cells
were more invasive compared to MCF-7 cells used in this study (Che et al 2013, Sun et
al 2014). Furthermore, the cultures were treated with 10-20 fold higher doses of
cyclopamine compared to the present study and higher concentrations of cyclopamine
have been documented previously to exhibit effects that are not specific to inhibition of
SMO (Zhang et al 2009, Che et al 2013). For the more metastatic breast cancer cell
lines, MDA-MB-231 and SKBR3, cyclopamine has been reported to inhibit cell
invasion and for other cancer cell lines such as the SW480 colorectal cancer cells,
cyclopamine also repressed cell invasion in association with decreased mRNA levels of
SLUG, SNAI1 and TWIST1 and increased E-cadherin levels, indicating inhibition or
reversal of EMT (Kameda et al 2009, Qualtrough et al 2015).
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In summary, DHT and cyclopamine treatments of MCF-7 and T-47D cells were found
to decrease the expression of a number of genes encoding regulators and mediators of
EMT. These included TGFβ and WNT signalling pathway intermediates, mediators of
cell-to-ECM interactions and EMT core transcription factors. In combination with the
upregulation of epithelial and downregulation of mesenchymal marker expression, this
pattern of gene expression indicated a reversal or inhibition of EMT, a hypothesis
supported by the reduced migration and invasion of DHT and cyclopamine treated
MCF-7 cells. Overall, results of this thesis study have shown that DHT and
cyclopamine treatments of breast cancer cells inhibit cellular processes that promote
progression of tumours, development of drug resistance and progression of EMT. The
findings support further investigation to determine whether targeting of the AR and
Hedgehog signalling pathways improves the efficacy of current breast cancer treatment
regimens and increases progression-free and overall survival.
Chapter 6
General Discussion
Chapter 6: General Discussion
198
6.1 General Discussion
Breast cancer associated mortality is most frequently due to re-initiation of tumour
growth and development of metastatic tumours despite initial success of disease
treatments. Tumour growth and metastasis result from the dysregulation of a number of
pathways including cell proliferation, apoptosis, drug resistance, EMT, cell migration,
cell invasion and initiation of tumour-associated angiogenesis. As such, combinations of
drugs that together inhibit these critical processes are likely to improve therapeutic
outcomes including progression-free and overall survival of breast cancer patients.
Underpinning the development and application of these treatment strategies is the
characterisation of pathways and associated mechanisms regulated by both current and
novel therapies, enabling selection of the most effective combinations of drugs for the
treatment of different breast cancer subtypes and individual tumours.
The uncontrolled growth of breast tumours resulting from aberrant regulation of the cell
cycle can be targeted by existing breast cancer therapies including chemotherapeutic
drugs and drug combinations (anthracyclines, taxanes, cyclophosphamide /
methotrexate / fluorouracil (CMF)), endocrine therapies (tamoxifen, fulvestrant,
aromatase inhibitors) and the anti-HER2 monoclonal antibody, trastuzumab, with
effects including induction of cell cycle arrest in G1/S or G2/M and cell cycle exit in
susceptible tumours (Le et al 2003, Pohl et al 2003, Dalvai and Bystricky 2010, Hallett
et al 2015). The ability of cells to proceed from G1 to M phase of the cell cycle is
modulated by appropriate expression of positive (e.g. cyclin D, cyclin E, cyclin-
dependent kinases (CDKs)) and negative regulators (CDK inhibitors, p21Cip1/Waf1,
p27Kip1), which when dysregulated, may stimulate cell growth (Deshpande et al 2005,
Wang et al 2009a). As these factors modulate distinct stages of the cell cycle, profiling
of their expression in breast tumours may be used as a predictive marker for responses
to established or novel breast cancer treatments (Kurebayashi et al 2011, Magbanua et
al 2015).
Chemotherapeutic agents, for example CMF (cyclophosphamide / methotrexate /
fluorouracil) that inhibit the proliferation of rapidly dividing cells by intercalating DNA,
impede the progression of cells from G1 to S phase, where DNA synthesis occurs (Pohl
et al 2003, Kurebayashi et al 2011). Expression of p27Kip1 may serve as a predictive
marker of response as breast tumours with low p27Kip1 expression respond poorly to
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199
CMF (Han et al 1999). The ER antagonist, tamoxifen, and the pure anti-oestrogen,
fulvestrant increase the proportion of MCF-7 cells in the G0/G1 phase of the cell cycle,
reflecting the mechanism of action of these treatments which is to repress ERα-
mediated expression of target genes, several of which are cell cycle regulators
(Lykkesfeldt et al 1984, Dalvai and Bystricky 2010). For example, inhibition of cell
proliferation induced by tamoxifen and fulvestrant are associated with downregulation
of E2/ER-mediated transcription of cyclin D1, c-Myc and cyclin E leading to the
accumulation of cells in the G1 phase of the cell cycle. This is associated with reduced
phosphorylation of retinoblastoma protein (Rb), elevated expression of p21Cip1/Waf1 and
p27Kip1, and reduced formation and activity of cyclin-CDK complexes (e.g. cyclin D1-
CDK4, cyclin E-CDK2) (Watts et al 1995, Cariou et al 2000, Dalvai and Bystricky
2010). Similar to tamoxifen, other SERMs such as raloxifene inhibit MCF-7 cell
proliferation by preventing transition of cells from G1 to S phase (Fryar et al 2006,
Shibata et al 2010).
The aromatase inhibitors, anastrazole and letrozole have also been shown to induce cell
cycle arrest in G0/G1 phase in MCF-7 cells (Itoh et al 2005). Recently, a newer group of
aromatase inhibitors (3β-hydroxyandrost-4-en-17-one, 5α-androst-2-en-17-one, androst-
4-en-17-one, 4α,5α-epoxyandrostan-17-one), which are chemically modified forms of
androstenedione, a substrate of aromatase, were identified to similarly inhibit cell cycle
progression, supporting the application of these agents for the treatment of human breast
tumours (Amaral et al 2013). In the study by Amaral et al, 3β-hydroxyandrost-4-en-17-
one and 5α-androst-2-en-17-one were shown to inhibit cell cycle progression from G1
to S phase, while androst-4-en-17-one and 4α,5α-epoxyandrostan-17-one increased the
number of cells in G2 phase, indicating that the aromatase inhibitors alter the cell cycle
via different mechanisms (Amaral et al 2013). Androgens have also been reported to
alter the expression of cell cycle regulators and induce accumulation of cells in G1
phase, with DHT treatment of MCF-7 cells decreasing expression of CDK2 and CDK4
but upregulating levels of the cell cycle inhibitor and AR target, p27Kip1 (Greeve et al
2004). In the present study, PCR array analysis of breast cancer-associated genes
indicated that DHT downregulated expression of cyclin D1, c-MYC as well as c-JUN,
which promote cell cycle progression.
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200
The expression of cell cycle regulators is modified by activation of signalling pathways
(e.g. MAPK, ERK, PI3K) following ligand binding to cell surface receptors (e.g. EGF,
IGF-1, TGFβ, Hedgehog, WNT), frequently promoting proliferation. For this reason,
inhibition of signalling pathways may be used to reduce proliferation, for example,
inhibition of PI3K signalling by the small molecule inhibitor, LY294002 downregulates
expression of cyclinD1/D3 and CDK4 in MCF-7 cells, impeding cell cycle progression
(Wang et al 2014). In the present and in previous studies (Che et al 2013), inhibition of
the Hedgehog signalling pathway by cyclopamine was shown to downregulate cyclin
D1 mRNA levels, which was correlated with MCF-7 cell cycle arrest in G1 phase and
inhibition of cell proliferation (Che et al 2013).
In line with the well-characterised abnormal expression of cell cycle regulators that are
evident in cancers, specific inhibitors of cell cycle regulators have been developed as
novel treatment strategies. For example, PD0332991 (palbociclib), an inhibitor of
CDK4 and CDK6 (CDK4/6), inhibits the proliferation of breast cancer cell lines,
including MCF-7 and the HER2-overexpressing SUM-190 and MDA-MB-361 cell lines
(Finn et al 2009). Due to its effects on CDK4/6 function, PD0332991 arrests the cell
cycle in G1 phase and reduces phosphorylation of Rb (Finn et al 2009). Three CDK4/6
inhibitors, palbociclib, abemaciclib, and LEE011 have entered clinical trials for solid
tumours including locally advanced and metastatic breast cancer, and results indicated
that the drugs were safe and prolonged progression-free survival of patients when
administered in combination with endocrine therapies (Bardia et al 2014, Patnaik et al
2014, Asghar et al 2015, Finn et al 2015). Supporting this novel strategy of direct
targeting of cell cycle progression, palbociclib was granted accelerated approval in
February 2015 for use in combination with the aromatase inhibitor, letrozole in
postmenopausal women with ER+ve/HER2-ve breast cancers (Finn et al 2015, Mayer
2015).
Cancer treatments that induce apoptosis frequently do so by regulation of the expression
of anti-apoptotic (e.g. BCL2) and pro-apoptotic (e.g. p53) regulators (Arun et al 2003,
Buchholz et al 2003). Mutation or altered expression of these regulators, which leads to
disruption of the balance between cell proliferation and apoptotic cell death,
contributing to tumour growth, similarly indicates low responsiveness of tumour cells to
a variety of therapies (Tabuchi et al 2009, AbuHammad and Zihlif 2013). Consistent
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201
with this hypothesis, BCL2 was markedly upregulated in MCF-7 cells selected for
resistance to doxorubicin, suggesting that elevated expression of BCL2 supports cell
growth in drug-resistant breast cancer cells (AbuHammad and Zihlif 2013). Tamoxifen,
fulvestrant and androgens such as DHT in the present study downregulate BCL2 and c-
MYC, and upregulate p53 mRNA levels in MCF-7, T-47D and ZR-75-1 cells,
supporting the inhibitory effects of these agents in breast cancer cells (Lapointe et al
1999, Zhang et al 1999, Thiantanawat et al 2003). Treatment of primary breast tumours
with the chemotherapeutic agents, docetaxel and doxorubicin also reduce expression of
BCL2 (Buchholz et al 2003), and natural compounds such as curcumin, a polyphenolic
compound found in the spice turmeric, which has been proposed as a cancer treatment,
elevated the ratio of the pro-apoptotic gene, BAX to anti-apoptosis (pro-survival) gene,
BCL2 in MCF-7 cells (Masuelli et al 2013).
Although current and novel therapies effectively inhibit proliferation and induce
apoptosis in breast cancer cells via regulation of expression of genes that encode
mediators of these processes, development of treatment resistance occurs frequently,
leading to regrowth of the tumours (Holohan et al 2013). Therapies given in
combination to patients have been shown to prolong resistance-free survival. For
example, treatment with the chemotherapeutic agents, doxorubicin, docetaxel and
cyclophosphamide as a combination decreased the occurrence of drug resistance in
patients with node-positive and early breast cancers (Mackey et al 2013). Similarly,
combinations of chemotherapy and trastuzumab (e.g. docetaxel / carboplatin /
trastuzumab) in HER2-overexpressing breast cancers increased time to disease
progression and improved patient survival (Valero et al 2011). In support of these
findings, trastuzumab, when combined with doxorubicin, epirubicin and paclitaxel was
found to exhibit additive inhibitory effects on in vitro and in vivo growth of the HER2-
overexpressing breast cancer cell lines, SK-BR-3 and MDA-MD-361 (Pegram et al
2004). Fulvestrant was also shown to increase the sensitivity of ER+ve MCF-7 and ZR-
75-1 cells to cytotoxic agents, taxanes (paclitaxel, docetaxel), doxorubicin, vinorelbine
and fluorouracil when fulvestrant was given in combination with the cytotoxic agents
(Ikeda et al 2011).
While treatment of breast cancer patients with multiple therapeutic drugs has been
successful in delaying development of drug resistance, patients may be given drugs that
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202
are unnecessary, or which result in side effects and toxicity that necessitate dose
reduction or early cessation of treatment, potentially accelerating disease progression.
Characterisation of the mechanisms underlying treatment resistance may improve the
selection of therapies or combinations of therapies that maximise the duration of
responses but minimise long-term impact on quality of life. Factors which have been
shown to engender drug resistance in cancers include disruption of mechanisms
associated with breakdown or metabolism of drugs, alteration of drug detoxification,
mutation or loss of expression of drug targets, aberrant activation of secondary
pathways and increased drug efflux (Housman et al 2014).
Targeted therapies and anti-cancer drugs are metabolised by enzymes such as the
cytochrome P450 (CYP) enzymes which, depending on the drug, either produce the
toxic or more toxic form of the drug, or alternatively detoxify it. For example, CYP2D6
metabolises tamoxifen to the active metabolites, 4-hydroxytamoxifen and endoxifen.
CYP2D6 is highly polymorphic and a number of CYP2D6 allelic variants (e.g.
CYP2D6*10, CYP2D6*9, CYP2D6*10, CYP2D6*17, CYP2D6*29, CYP2D6*36,
CYP2D6*37, CYP2D6*41) have been associated with reduced function of CYP2D6
(Marez et al 1997, Sachse et al 1997, Borges et al 2006). In women who express the
CYP2D6*10 variant, serum levels of 4-hydroxytamoxifen were found to be lower and
disease-free survival rates were also poorer following tamoxifen treatment, compared to
women expressing more highly active CYP2D6 alleles (Xu et al 2008). Another CYP
enzyme, CYP3A4 detoxifies docetaxel and elevated expression of CYP3A4 in recurrent
breast tumours has been associated with poorer responses of the tumours to docetaxel
(Sakurai et al 2011). Hence, profiling of the expression of drug metabolising enzymes
may predict tumour responsiveness to therapy and allow for more appropriate treatment
selection. Inhibitors of CYP3A4 (e.g. ritonavir) in combination with chemotherapy have
been evaluated in human breast tumours but side effects associated with the drug
combinations suggest the need for development of alternative drugs to target this CYP
enzyme (Swiecicki et al 2013).
A number of drugs bind specifically to their cellular targets (e.g. oncoproteins, hormone
receptors) to exhibit their effects, but mutations or altered conformation of these drug
targets reduce binding or binding affinity and constitute a major mechanism of drug
resistance. In breast cancer, mutations, for example, in the oestrogen receptor gene,
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203
ESR1, and HER2, have been reported to reduce binding affinities or prevent binding of
anti-oestrogens to ERα and anti-HER2 monoclonal antibodies to HER2, resulting in
resistance to the targeted therapies (Anido et al 2006, Mitra et al 2009, Merenbakh-
Lamin et al 2013, Rexer et al 2013, Robinson et al 2013, Jeselsohn et al 2014). For
example, in HER2-overexpressing breast tumours, p95HER2, a truncated form of HER2
which lacks the binding region for trastuzumab, confers resistance of tumours to
trastuzumab (Anido et al 2006). Other examples of mutations affecting binding of
therapeutic drugs similarly contribute to drug resistance. The EGFRT790M mutation in
the EGFR kinase domain in lung adenocarcinomas decreases binding of the EGFR
tyrosine kinase inhibitors, gefitinib and erlotinib, resulting in drug resistance, while
secondary mutations in the BCR-ABL fusion gene (e.g. BCR-ABLT315I) induce
conformational changes in BCR-ABL and prevent binding of imatinib, an Abelson
tyrosine kinase inhibitor, leading to imatinib resistance (Shah et al 2002, Pao et al
2005). To overcome this form of resistance, novel therapeutic drugs targeting
EGFRT790M and BCR-ABLT315I mutations have been developed (Noronha et al 2008,
Sequist et al 2015), and pre-clinical and clinical studies have also shown that binding of
lapatinib to p95HER2 reduced tumour growth and improved overall survival of patients
with p95HER2 expressing tumours (Scaltriti et al 2007, Hutchinson 2010, Scaltriti et al
2010).
Anti-oestrogens including tamoxifen are often successful in the treatment of ERα-
expressing breast tumours but drug resistance can occur, with a proportion of the
tamoxifen-resistant tumours (~17%) shown to have become ERα-ve (Johnston et al
1995, Gutierrez et al 2005). One mechanism by which ERα expression may be
downregulated is by epigenetic modification (e.g. DNA methylation, histone
deacetylation) of the ERα gene, ESR1. DNA methylation induces re-organisation of the
chromatin structure which reduces binding of transcriptional regulators and hence
represses gene transcription (Bird 2002, Leu et al 2004). In breast cancer,
hypermethylation of a CpG island encompassing the ESR1 promoter, which decreases
ERα expression, has been demonstrated in ERα-ve but not in ERα+ve breast tumours
(Kim et al 2004). Inhibition of DNA methyltransferase, an enzyme which catalyses
DNA methylation, by 5’-aza-2’-deoxycytidine (deoxyC) was reported to re-activate
ERα expression in ER-ve breast cancer cells, MDA-MB-231, and similarly, inhibition
of histone deacetylases increased ERα expression in MDA-MB-231 cells and enhanced
their sensitivity to 4-hydroxytamoxifen (Sharma et al 2005, Zhou et al 2007).
Chapter 6: General Discussion
204
Supporting the findings of these experimental studies, a clinical trial evaluating a
combination of tamoxifen and the histone deacetylase inhibitor, vorinostat in tamoxifen-
resistant breast tumours reported that vorinostat increased the responses of tumours to
tamoxifen (Munster et al 2011).
An alternative mechanism that promotes drug resistance in breast cancers is aberrant
activation and expression of intermediates of secondary pathways that stimulate tumour
growth. For example, the EGFR/HER2 pathway has been implicated in resistance of
ER+ve breast tumours to anti-oestrogens (Shou et al 2004, Massarweh et al 2008).
EGFR and HER2 protein expression as well as levels of phosphorylated (activated)
p42/p44 and p38 MAPKs, which are downstream intermediates of EGFR/HER2
signalling, were shown to be upregulated in tamoxifen-resistant MCF-7 xenograft
(murine) models. Treatment of the mice with gefitinib, a TKI which inhibits EGFR, in
combination with tamoxifen delayed the time to tamoxifen resistance, supporting
involvement of this secondary signalling mechanism (Massarweh et al 2008).
Development of resistance to trastuzumab has been associated with hyperactivation of
PI3K/AKT signalling and elevated expression of IGF1R (Berns et al 2007, Dieras et al
2007, Browne et al 2011). Increased PI3K/AKT signalling which is indicated by loss of
PTEN expression was observed in the trastuzumab-resistant BT-474 breast cancer cell
line (Berns et al 2007). Additionally, expression of IGF1R was elevated in SKBR3 cells
that were selected for resistance to trastuzumab, with inhibition of IGF1R by siRNA in
combination with trastuzumab shown to reduce cell proliferation. As IGF1R-siRNA and
trastuzumab individually had little effects on cell proliferation, these findings indicated
that inhibition of IGF1R enhanced the responsiveness of trastuzumab-resistant SKBR3
cells to trastuzumab (Browne et al 2011). Overall, blocking of multiple signalling
pathways can potentially delay development of resistance, however use of inhibitors of
multiple pathways is also likely to increase side effects and this needs to be balanced
with benefits associated with the treatments such as improvement in disease-free and
overall survival.
Drug resistance is also caused by overexpression of the ABC drug efflux transporters
which are capable of exporting a variety of drugs especially chemotherapeutic agents.
Overexpression of ABCB1 and ABCG2 was initially identified in cancer cell lines
including MCF-7 cells which had been selected for resistance to doxorubicin and
Chapter 6: General Discussion
205
mitoxantrone, implicating the ABC transporters in the development of drug resistance
(Roninson et al 1986, Doyle et al 1998, Miyake et al 1999). As such, downregulation of
the expression and function of these transporters would be expected to delay or prevent
ABC transporter-mediated resistance of tumours. In support of this hypothesis,
treatment of doxorubicin-resistant and ABCB1-overexpressing MCF-7 cells (MCF-
7/Adr) with the ABCB1 inhibitor, verapamil increased the sensitivity of cells to the
cytotoxic effects of doxorubicin (Mealey et al 2002). The proliferation of ABCG2-
transfected MCF-7 cells, which were resistant to mitoxantrone cytotoxicity, was
decreased following co-treatment of the cells with the ABCG2 inhibitor, fumitremorgin
C (FTC), indicating that FTC reversed ABCG2-mediated resistance of MCF-7 cells to
mitoxantrone (Rabindran et al 2000). A number of ABC transporter inhibitors (e.g.
Zosuquidar, Elacridar, Tariquidar) have been developed but in clinical studies of
cancers including breast cancer, small cell lung cancer and acute myeloid leukaemia
(AML), these agents did not improve responses of cancers to chemotherapy (e.g.
doxorubicin, vincristine, topotecan) or increase overall survival despite successes of
these agents in enhancing the sensitivity of cancer cells and tumours to
chemotherapeutic agents in pre-clinical and early clinical studies (Mistry et al 2001,
Kruijtzer et al 2002, Gerrard et al 2004, Pusztai et al 2005, Kuppens et al 2007,
Morschhauser et al 2007, Saeki et al 2007, Cripe et al 2010). Of note, the ABC
transporter inhibitors evaluated in clinical trials were predominantly inhibitors of
ABCB1 and only a few of these such as elacridar were shown to cross-react with
ABCG2 (Kruijtzer et al 2002).
A growing number of studies have identified that inhibitors of signalling pathways (e.g.
PI3K/AKT, MAPK/ERK (MEK), Hedgehog, WNT), clinically available targeted drugs
(e.g. tyrosine kinase inhibitors) and natural compounds (e.g. vitamin D3, curcumin) are
capable of downregulating ABC transporter expression and/or function and may
therefore be evaluated as treatments to reverse ABC transporter-mediated drug
resistance in breast tumours (Chearwae et al 2006, Katayama et al 2007, Dai et al 2008,
Chikazawa et al 2010, Goler-Baron et al 2012, Wei et al 2012). For example, the PI3K
inhibitor, LY294002 did not alter ABCG2 protein levels but increased the sensitivity of
mitoxantrone-resistant MCF-7 cells (MCF-7/MX) to the ABCG2 substrates,
mitoxantrone and topotecan, which may be attributed to inhibition of ABCG2 efflux
activity (Goler-Baron et al 2012). Treatment of ABCB1-transfected MCF-7 and MDA-
MB-231 cells, which were resistant to paclitaxel, with the MEK inhibitor, U0126,
Chapter 6: General Discussion
206
downregulated ABCB1 expression and elevated paclitaxel cytotoxic effects in the cells
(Katayama et al 2007). In this study, the androgen ligand, DHT downregulated ABCG2
mRNA and protein expression in MCF-7 cells and this was associated with increased
sensitivity to mitoxantrone, and although the Hedgehog signalling inhibitor,
cyclopamine did not alter ABCG2 expression, the decreased ABCG2 localisation to
membrane-associated complexes induced in cyclopamine-treated MCF-7 cells was
associated with increased sensitivity of the cells to mitoxantrone, presumably via
inhibition of ABCG2 efflux function.
In cell lines, resistance to therapeutic agents is frequently associated with
overexpression of ABC transporters however in human breast tumours, ABC
transporters are not markedly overexpressed although their expression is generally
correlated with poorer responses to chemotherapy (Kanzaki et al 2001, Faneyte et al
2002, Burger et al 2003, Yuan et al 2008). Recent research has identified that ABC
transporters, in particular ABCG2 are overexpressed in breast cancer stem cells and in
cancer stem cells of other tumour types (Kim et al 2002, Engelmann et al 2008, Zhang
et al 2013a, Guzel et al 2014). Overexpression of ABC transporters in cancer stem cells
protects the stem cells from exogenous and endogenous toxic influences as solid
tumours frequently contain regions of necrosis and apoptosis, with an inefficient blood
supply to remove metabolic toxins and toxins produced by dead and dying cells (Dean
et al 2005). The high levels of ABC transporter expression also confer resistance of
stem cells to therapeutic drugs, allowing the cancer stem cells to “differentiate” into
cancer cells and initiate tumour relapse (Kim et al 2002, Ding et al 2010, Jiang et al
2012). Therefore, therapeutic strategies to deplete or eliminate the cancer stem cell
population or to reduce its chemoresistance are important for prolonging recurrence-free
and thus overall survival. In previous studies, inhibition of pathways associated with
stem cell development including the Hedgehog, WNT and NOTCH pathways has been
shown to decrease the proliferation of cancer stem-like cells and to curb in vitro and in
vivo tumorigenesis associated with these cells (Bar et al 2007, Chikazawa et al 2010,
McAuliffe et al 2012). Inhibitors of NOTCH and WNT signalling are also being
investigated in clinical trials for breast cancer and for other solid tumours
(ClinicalTrials.gov Identifier: NCT01616758, NCT01345201). In the present study,
DHT was found to downregulate ABCG2 expression and membrane-associated
localisation of ABCG2 in breast cancer stem-like cells isolated from the MCF-7 breast
cancer cell line which, based on results from parental MCF-7 cells, may increase the
Chapter 6: General Discussion
207
sensitivity of the stem-like cells to mitoxantrone. Although cyclopamine did not
markedly alter total ABCG2 protein levels, the treatment reduced ABCG2 levels in
membrane-associated complexes in breast cancer stem-like cells, indicating that
inhibition of the Hedgehog pathway may also affect sensitivity to chemotherapeutic
agents by modulating ABCG2 localisation. Thus, potential beneficial effects of adjunct
treatments with androgens or Hedgehog signalling inhibitors may be in part mediated
by their downregulation of ABC transporter efflux activity and consequent increase in
chemosensitivity of both breast cancer cells and breast cancer stem cells.
Tumour metastasis is a major cause of breast cancer-related death. Patients with
metastatic breast tumours are treated with chemotherapy, hormonal therapies or anti-
HER2 monoclonal antibodies depending on the breast cancer subtype and the general
health of the patient, however, the disease commonly relapses. As combination
therapies have been shown to improve treatment efficacy, adjunct or additional
therapies that extend the progression-free survival of patients with advanced breast
cancer are constantly evaluated. A number of inhibitors of signalling pathways such as
the PI3K/AKT/mTOR and IGF pathways are currently in or have recently been
investigated in clinical trials for metastatic breast cancer (Robertson et al 2013, Qiao et
al 2014, Gonzalez-Angulo et al 2015). However, growth factor inhibitors are often
associated with treatment resistance and worse treatment outcome due to activation of
other growth factor family members to sustain tumour growth (Haluska et al 2007, Lo
et al 2007, Robertson et al 2013). For example, treatment of metastatic breast cancer
patients with the anti-IGF1R monoclonal antibody, ganitumab, in combination with the
anti-oestrogen, fulvestrant or the aromatase inhibitor, exemestane, in a phase II clinical
trial, was shown to result in shorter progression-free survival compared to patients
treated with the hormonal therapy alone (Robertson et al 2013). It has been proposed
that inhibition of IGF1R may induce expression of growth hormone and IGF1 to
support the continued growth of breast tumours (Haluska et al 2007).
EMT is a developmental programme which induces the transition of epithelial-like cells
into mesenchymal-like cells that have enhanced abilities to migrate and invade. During
tumour progression to metastasis, EMT is commonly induced, allowing tumour
dissemination from the original tumour site to a new site or organ, where MET, the
reverse process of EMT, is activated to allow growth of the metastatic tumour deposit.
Chapter 6: General Discussion
208
The processes involved in EMT that modify the tumour cells and their surrounding
stroma are regulated by signalling pathways (e.g. TGFβ, WNT, NOTCH). Therefore,
inhibition of EMT-associated signalling pathways and processes may delay the
development of metastatic tumours and improve progression-free and overall survival, a
treatment strategy that is being assessed in experimental models and early clinical trials.
For example, in a mouse model of breast cancer bone metastasis, the anti-TGF-β1
antibody, ID11 decreased tumour burden in bone and reduced the number of osteolytic
lesions (Biswas et al 2011). Withaferin A (WFA), an extract from the plant Withania
somnifera inhibited MDA-MB-231 breast cancer cell migration and invasion by
inducing depolymerisation of the EMT marker and cytoskeletal element, vimentin
(Thaiparambil et al 2011). Intetumumab, an anti-αV integrin monoclonal antibody was
reported to decrease the formation of brain metastases in mice transplanted with
metastatic breast cancer cells, 231BR-HER2 (Wu et al 2012b). Phase I and II clinical
trials for intetumumab have been carried out for advanced solid tumours including
breast and prostate cancers and melanoma, with the agent shown to be safe, without
major cytotoxicity and to improve overall patient survival when combined with
chemotherapy (Mullamitha et al 2007, Chu et al 2011, O'Day et al 2011). Results from
this thesis indicated that DHT and cyclopamine treatments repressed EMT as genes
which encode mediators of EMT-inducing signalling pathways (TGFβ, WNT) and ECM
components were markedly downregulated, with these findings supported by the
suppression of migration and invasion of MCF-7 cells. The inhibition of multiple facets
of the EMT programme by DHT and cyclopamine provide evidence for further
development of androgens and Hedgehog signalling inhibitors as adjunct therapies that
impede breast tumour progression to metastatic disease.
Angiogenesis is another process essential for tumour progression as it promotes
development and assembly of the blood vasculature, a critical source of nutrients
required for tumour growth (Kerbel 2008). Regulators of angiogenesis include vascular
endothelial growth factors (VEGF), fibroblast growth factors (FGF), platelet derived
growth factors (PDGF) and their receptors, and intermediates of signalling cascades
(e.g. Delta/Notch) (Hicklin and Ellis 2005, Lieu et al 2011, Heldin 2013, Zhou et al
2013). Combinations of anti-angiogenesis agents such as the humanised monoclonal
antibody targeting VEGF-A, bevacizumab, or small molecule inhibitors of VEGFR and
PDGFR, sorafenib and sunitinib, with anti-oestrogens, trastuzumab or chemotherapy
have been shown in pre-clinical studies to delay tumour progression (Qu et al 2008,
Chapter 6: General Discussion
209
Coxon et al 2009). For example, overexpression of VEGF in MCF-7 cells was
associated with development of resistance to tamoxifen and formation of lung
metastases in mouse xenograft models, indicating the importance of tumour-associated
angiogenesis in disease progression (Qu et al 2008). When mice transplanted with
MCF-7 cells were treated with a combination of tamoxifen and motesanib, a muti-
targeted inhibitor of VEGFR1, VEGFR2, VEGFR3, PDGFR and c-KIT, inhibition of
tumour growth was enhanced compared to either treatment alone (Coxon et al 2009).
These studies support inclusion of agents which inhibit angiogenesis pathways to
treatment of breast cancer in order to delay tumour progression. In this study, DHT and
cyclopamine downregulated expression of the angiogenesis-inducing regulators, JUN,
NOTCH1 and inhibitor of DNA binding 1 (ID1), and the effects of these treatments on
tumour-associated angiogenesis may be evaluated in future studies using MCF-7
xenografts grown in immunosuppressed mice.
Several clinical trials have assessed combinations of angiogenesis inhibitors with
established breast cancer therapies. For example, a phase III study of bevacizumab and
letrozole in ER+ve advanced breast cancer showed that the combination of these agents
increased progression-free survival of patients (Dickler et al 2015). An ongoing study is
similarly evaluating bevacizumab and letrozole or fulvestrant in locally recurrent or
metastatic ERve/PR+ve/HER2-ve breast cancers (Martín et al 2013). Several previous
clinical trials investigating the combination of bevacizumab with chemotherapy and/or
trastuzumab produced disappointing results with small effects on progression-free
survival and no improvement in overall survival (Miller et al 2007, Miles et al 2010,
Robert et al 2011, Smith et al 2011, Brufsky et al 2012). However, the combination of
bevacizumab, trastuzumab and docetaxel in HER2-overexpressing breast cancers was
found to increase progression-free survival of patients with tumours expressing VEGF-
A, suggesting that only a proportion of breast cancer patients would benefit from
treatment regimens that include bevacizumab (Gianni et al 2013). Similarly, in
experimental studies, VEGF-overexpressing MCF-7 xenografts were found to be more
sensitive to the effects of bevacizumab compared to xenografts of parental MCF-7 cells
(Gokmen-Polar et al 2014). These findings indicate that use of biomarkers, for example
VEGF expression may be required to select patients whose breast tumours would
respond most favourably to bevacizumab-containing treatment combinations.
Chapter 6: General Discussion
210
Tumour progression is regulated by a number of processes, including cell proliferation,
suppression of apoptosis, drug resistance, cell migration/invasion, EMT and
angiogenesis, and therefore optimal treatment would involve a combination of
therapeutic drugs that target as many of these pathways as possible to improve
progression-free and overall survival of patients. To enhance the efficacy of treatment
regimens, the aim for cancer management is the development and refinement of
personalised therapy, whereby treatment combinations are tailored to individual patients
and their tumours. Although this goal has not yet been achieved, considerable
improvements have been made in our understanding of mechanisms associated with
tumour progression. These have led to the development of a number of novel agents that
have been or are being evaluated in pre-clinical and clinical trials as well as
identification of previously uncharacterised effects mediated by current therapeutic
agents that pre-empt modification of their clinical use. Implementation of personalised
cancer therapies by definition requires the establishment of biomarkers that predict
sensitivity or resistance to individual and combinations of treatments as well as disease
prognosis. Underpinning these advances in the clinical application of novel therapies is
a comprehensive knowledge of the mechanisms of action of current and novel agents to
devise the appropriate application of the drugs and drug combinations for different
stages and subtypes of breast tumours. Results of this thesis describing the effects of
androgens and Hedgehog signalling inhibitors on pathways that contribute to breast
cancer progression add to this knowledge, thereby indicating how these agents can
contribute to treatment regimens already established or under development.
Implementation of androgens and/or Hedgehog signalling inhibitors in breast cancer
management will require additional in vitro and in vivo studies that similarly evaluate
members of these classes of pharmaceutical agents that are able to be administered to
humans as well as biomarkers of treatment sensitivity or resistance.
6.2 Future Directions
In this study, AR- and Hedgehog pathway-mediated regulation of breast cancer-
associated genes, including genes encoding the ABCG2 drug efflux transporter and
EMT regulators were evaluated by treatment of MCF-7 and T-47D cells with the
androgen, 5α-dihydrotestosterone (DHT) and the small molecule Hedgehog pathway
inhibitor, cyclopamine. More extensive analysis of ABCG2 and EMT showed that DHT
Chapter 6: General Discussion
211
and cyclopamine treatments downregulated ABCG2 expression and efflux activity as
well as suppressing the expression of EMT-associated genes and inhibiting cell
migration and invasion. As DHT and cyclopamine are not suitable for clinical use, in
future studies, additional androgens and Hedgehog signalling inhibitors, especially
those that are pharmacologically applicable such as the selective androgen receptor
modulator (SARM), enobosarm and the Hedgehog/SMO inhibitor, vismodegib or GDC-
0449 may be tested in vitro (Gao and Dalton 2007, Dalton et al 2011, LoRusso et al
2011, Sandhiya et al 2013, Overmoyer et al 2014).
PCR arrays or cDNA microarrays may be used initially to screen for genes and cellular
processes potentially regulated by the agents, with dose responses and additional
timepoints providing a more comprehensive analysis of regulation of gene expression
following treatment of breast cancer cells. Additional cell lines representing other breast
cancer cell types (e.g. molecular apocrine, triple-negative breast cancer (TNBC)) may
be screened to indicate the subtypes of breast cancer potentially sensitive or resistant to
these treatment strategies (Perou et al 1999, Sorlie et al 2001, Sorlie et al 2003, Farmer
et al 2005, Prat et al 2010, Ciriello et al 2013). Importantly, comparison with DHT and
cyclopamine regulated genes identified in the present study will help to identify genes
that are commonly regulated by the androgen/AR and Hedgehog signalling pathways as
opposed to genes regulated by specific androgens or Hedgehog signalling inhibitors
whose effectiveness may be more dependent on co-factor and other gene expression in
individual tumours. Results from the microarrays would also allow identification of
biomarkers of tumour responses which are relevant for downstream clinical application
of these treatments. As targeted agents have frequently been shown to exhibit greater
efficacy when administered with other classes of drugs, androgens and Hedgehog
signalling inhibitors would also be evaluated in combination with chemotherapy or
endocrine therapies, for example, anti-oestrogens (e.g. tamoxifen, fulvestrant) and
aromatase inhibitors (e.g. anastrazole, letrozole) to detect potential additive, synergistic
or antagonistic effects associated with these drug combinations (Albain et al 2009,
Andersson et al 2011, Bedognetti et al 2011, Ramaswamy et al 2012, Chai et al 2013,
Sabol et al 2014).
Regulation of expression, intracellular localisation and efflux activity of drug
transporters, including ABCG2, ABCB1 and ABCC1 following short and long-term
Chapter 6: General Discussion
212
treatment of breast cancer cell lines with novel androgens and Hedgehog signalling
inhibitors should be evaluated to determine whether the agents are potential substrates
of one or more of the transporters and whether, similar to DHT and cyclopamine, they
downregulate the levels of active transporter function in breast cancer cells, increasing
the efficacy of chemotherapeutic or other targeted agents. Considering the importance
of breast cancer stem cells in tumour relapse and the development of drug resistant
disease, the specific responses of breast cancer stem cells isolated from breast cancer
cell lines to androgens and Hedgehog signalling inhibitors should be evaluated
(Visvader and Lindeman 2008, Han et al 2013). For such studies, stem-like cells may be
isolated from the breast cancer cell lines using similar methods to those employed in
this thesis (Hoechst 33342lo/CD44hi/CD24lo) (Kim et al 2002, Patrawala et al 2005,
Engelmann et al 2008, Yin et al 2008). In addition to characterisation of the levels and
localisation of the ABC transporters in the treated cells, the effects of androgen and
Hedgehog signalling inhibitor treatments on proliferation, sensitivity to
chemotherapeutic agents and the ability of stem cells to form tumours (xenografts) (see
below) in mice will indicate potential therapeutic advantages in the implementation of
this treatment regimen for breast cancer management (Al-Hajj et al 2003, Patrawala et
al 2005, Yin et al 2008).
In this study, investigation of the expression of EMT-associated genes using RT2
Profiler Human EMT PCR Arrays revealed that DHT and cyclopamine predominantly
downregulated expression of genes which encode components or intermediates of
EMT-inducing processes (cell-to-ECM interaction, degradation of the ECM) and
signalling pathways (TGFβ, WNT). The same methods may be used to investigate
whether other androgens and Hedgehog signalling inhibitors similarly regulate the EMT
programme. Following validation of these results by RT-qPCR and western blotting,
effects of the treatments on cell migration and invasion, hallmarks of cancer cells that
have undergone EMT, should be evaluated. To determine potential reversal of EMT by
androgen and Hedgehog signalling inhibitor treatments of breast cancer cells, EMT may
be stimulated in epithelial-like breast cancer cell lines (MCF-7 and T-47D) by culture
with TGF-β1 or overexpression of WNT ligands (Yook et al 2005, Lv et al 2013). The
effects of co-treatment with androgens or Hedgehog signalling inhibitors on expression
of EMT or TGFβ/WNT signalling associated genes, epithelial/mesenchymal
morphology, and cell migration and invasion would indicate whether these agents
would be effective in more aggressive breast cancers in which EMT is being driven by
Chapter 6: General Discussion
213
abnormal regulation of pro-EMT signalling. Expression of the intermediates of TGFβ
and WNT pathways may also be evaluated following androgen and Hedgehog
signalling inhibitor treatments to determine the mechanisms by which the treatments
regulate TGFβ or WNT-induced EMT.
Development of androgens and Hedgehog signalling inhibitors as adjunct therapies for
breast cancer is an important future direction of this research, and to generate pre-
clinical data, these agents will need to be evaluated in animal models (e.g. mice) in
which the tumour microenvironment more closely reflects that in humans. Mouse
xenograft models may be established by transplantation of breast cancer cell lines into
the mammary glands of mice to generate tumours in which to investigate responses to
androgens and/or Hedgehog signalling inhibitors. For these studies, tumour-bearing
mice would be administered with the treatments at doses which have been used in
clinical trials for breast cancer or other malignancies (Wang et al 2005, Masuelli et al
2013, Sandhiya et al 2013, Overmoyer et al 2014). The mouse models would also be
able to be used to determine effects of androgens and/or Hedgehog signalling inhibition
in combination with chemotherapy or targeted therapies (tamoxifen, aromatase
inhibitors, trastuzumab), with endpoints of tumour growth measured by tumour size and
weight, and immunohistochemical analysis of marker expression (e.g.
ER/PR/AR/HER2, EMT intermediates, proliferation markers). These results will
indicate the subtypes of breast tumours that would benefit from androgens and
Hedgehog signalling inhibitor treatments.
As results from this study indicate that androgens and Hedgehog signalling inhibitors
may inhibit the development of drug resistance and metastasis, tumour responses to
chemotherapeutic agents and formation of metastatic lesions in vivo may be evaluated
following treatment of host animals (e.g. mice) with combinations of chemotherapeutic
agents, androgens and Hedgehog signalling inhibitors. In vivo models of drug resistant
cancers have been generated in previous studies, for example, by transplanting
mitoxantrone-resistant breast cancer cell lines into mice (Kasibhatla et al 2007, Ma et al
2013). These models may be used to investigate whether co-treatment of the mice with
androgens or Hedgehog signalling inhibitors enhances tumour responsiveness to
chemotherapeutic agents (ie. diminishes chemoresistance). Evaluation of the expression
of the ABC transporters including ABCG2 in the tumours (xenografts) may also be
Chapter 6: General Discussion
214
performed to identify whether androgens and Hedgehog signalling inhibitors similarly
regulate ABC transporter expression and localisation in vivo as observed in breast
cancer cell lines in this study. Formation of metastatic tumours in vivo may also be
investigated following treatment of mice transplanted with breast cancer cell lines with
androgens and Hedgehog signalling inhibitors. As MCF-7 and T-47D cells rarely
develop metastases in vivo, EMT may be induced by treatment with TGF-β1 or
overexpression of N-cadherin or WNT ligands prior to transplantation into mice and
time to development of metastatic lesions may be compared between treatment groups
(Hazan et al 2000, Yook et al 2005, Lv et al 2013).
Evaluation of the efficacy of androgens and Hedgehog signalling inhibitors may
subsequently be performed in clinical trials if findings from in vitro and in vivo studies
support the administration of these agents to breast cancer patients. Based on results
from in vitro and in vivo studies, participants would be selected according to disease
stage, breast cancer subtype and expression of tumour biomarkers (e.g. AR, ER, HER2,
GLI1/2) to indicate likely responsiveness to androgens and Hedgehog signalling
inhibitors. Following experimental evidence from this thesis, from previous studies, and
from previous clinical use of these agents, therapeutic efficacy of combining androgens
and/or Hedgehog signalling inhibitors with chemotherapy or targeted therapies will be
determined to identify improvement in progression-free survival and overall survival.
Side effects and toxicity associated with these drug combinations will also be recorded
to determine the tolerability and safety of the drugs for routine human usage.
Conclusion
This thesis study has demonstrated that DHT and cyclopamine treatments of breast
cancer cells antagonise ABCG2-mediated drug efflux and EMT, processes that drive
chemoresistance and tumour metastasis. The findings support development of
androgens and Hedgehog signalling inhibitors as adjunct therapies for susceptible breast
tumours, a treatment strategy that will potentially delay disease progression and prolong
overall survival.
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Appendix 1
264
APPENDIX 1 BUFFERS & SOLUTIONS
1. 2% (w/v) Agarose
Agarose powder 6g
1× TAE52 300mL
10mg/mL Ethidium bromide20
8μL
Agarose and 1× TAE were heated in a microwave to dissolve the agarose. Ethidium bromide was added and the solution was stored at room temperature. Prior to use, agarose was heated in a microwave until melted, then cooled to ~70ºC before pouring into gel casting trays.
2. 1mg/mL 7-Aminoactinomycin D (7-AAD)
7-AAD 1mg
Methanol 50μL
PBS (with Ca2+and Mg2+)33
950μL
7-AAD was dissolved in methanol, PBS was added and the solution was stored at 4ºC protected from light.
3. 10% (w/v) Ammonium Persulphate (APS)
APS 0.1g
ddH2O 1mL
Ammonium persulphate was dissolved in ddH2O and the solution was stored at 4ºC for up to 2 weeks.
4. Blocking Buffer
Bovine serum albumin (BSA)
0.1g
Horse serum 1mL
10% Sodium azide45 2mg
PBS32 9mL
BSA was dissolved in PBS, the solution combined with horse serum and sodium azide and stored at 4ºC protected from light.
5. 10mg/mL Bromophenol Blue
Bromophenol blue 10mg
ddH2O 1mL
Bromophenol blue was dissolved in ddH2O and the solution was stored at room temperature.
6. 12mM Calcium Chloride
Calcium chloride 0.133g
ddH2O 100mL
Calcium chloride was dissolved in ddH2O and the solution was filtered through a 0.2µm filter, autoclaved, and stored at room temperature.
7. Cell Lysis Buffer (Subcellular
Fractionation)
1M Tris pH859 10μL
4M Sodium chloride46 2.5μL
2M Magnesium chloride27
1.5μL
NP40 5μL
Appendix 1
265
ddH2O 951μL
200mM PMSF31 5μL
40× Protease inhibitor cocktail37
25μL
Tris, sodium chloride, magnesium chloride, NP40 and ddH2O were combined in a 1.5mL tube and immediately before use, PMSF and protease inhibitors were added.
8. 50mM Chloroquine
Chloroquine 257mg
ddH2O 10mL
Chloroquine was dissolved in ddH2O in a laminar flow hood and the solution was stored protected from light at room temperature.
9. 20mg/mL Cyclopamine
Cyclopamine 20mg
100% Ethanol 1mL
Cyclopamine was dissolved in 100% ethanol and the solution was stored at -20ºC.
10. 1mM Cyclopamine
Cyclopamine (20mg/mL)9
2.06μL
100% Ethanol 97.94μL
Cyclopamine and ethanol were combined and the solution was stored at -20ºC.
11. Developer Solution
Solution A (1L)
Solution B (0.25L)
ddH2O 1.25L
Solution A and ddH2O were combined and then solution B added. Developer was stored at room temperature.
12. 10-2M DHT
5α-dihydrotestosterone (DHT)
0.0029g
100% Ethanol 1mL
DHT was dissolved in ethanol and the solution was stored at -20ºC. 10-
2M DHT was serially diluted in 100% ethanol as required and stored at -20ºC.
13. 2.72 kunitz units/µL DNase
DNase 1500 kunitz
units
ddH2O 551.5µL
DNase was dissolved in ddH2O and the solution stored at 4ºC.
14. 1kb Plus DNA Ladder™
1kb Plus DNA ladder™
50μL
6× DNA loading buffer15
166.7μL
Storage buffer49 783.3μL
1kb Plus DNA ladder™, 6× loading buffer and storage buffer were combined and the solution was stored in 1mL aliquots at -20ºC.
15. 6× DNA Loading Buffer
Sucrose 3.5g
0.1M EDTA18 5mL
Bromophenol blue 100μL
Appendix 1
266
(10mg/mL)5
Sucrose was dissolved in 0.1M EDTA, bromophenol blue was added, and the solution stored at room temperature.
16. 10mM dNTP Mix
dATP (100mM) 10μL
dTTP (100mM) 10μL
dCTP (100mM) 10μL
dGTP (100mM) 10μL
ddH2O 60μL
dATP, dTTP, dCTP, dGTP and ddH2O were combined and the solution was stored in 20µL aliquots at -20ºC.
17. Enhanced Chemiluminescence (ECL)
Solution A
Solution B
Equal volumes of solution A and solution B were combined as required. ECL was prepared immediately prior to use.
18. 0.5M EDTA pH8.0
EDTA 186.12g
Sodium hydroxide pellets
20g
ddH2O 1L
EDTA and sodium hydroxide pellets were dissolved in ~500mL ddH2O, the pH adjusted to 8.0 and the solution made up to 1L with ddH2O, autoclaved and stored at room temperature. 0.5M EDTA was diluted as required in ddH2O.
19. 70% / 75% / 95% Ethanol (EtOH)
95% 75% 70%
100% Ethanol
95mL 75mL 70mL
ddH2O 5mL 25mL 30mL
Ethanol and ddH2O were combined and the solution was stored at room temperature.
20. 10mg/mL Ethidium Bromide
Ethidium bromide 10mg
ddH2O 1mL
Ethidium bromide was dissolved in ddH2O and the solution was stored at room temperature protected from light.
21. Fixer Solution
Solution A (0.5L)
ddH2O 2L
Solution A was added to ddH2O and the solution shaken to combine. Fixer was stored at room temperature.
22. 4% (v/v) Formaldehyde
40% Formaldehyde 1mL
PBS32 9mL
Formaldehyde and PBS were combined and the solution was stored at room temperature.
23. 5mg/mL Hoechst 33342
Hoechst 33342 25mg
ddH2O 5mL
Hoechst 33342 was dissolved in ddH2O and the solution was stored
Appendix 1
267
in 100µL aliquots at -20ºC protected from light.
24. 1M Hydrochloric Acid (HCl)
10M HCl 10mL
ddH2O 90mL
HCl and ddH2O were combined and the solution was stored at room temperature.
25. 5mg/mL KO143
KO143 1mg
DMSO 200μL
KO143 was dissolved in DMSO and the solution was stored at -20ºC.
26. 1mM KO143
KO143 (5mg/mL)25 9.4µL
DMSO 990.6μL
KO143 was diluted in DMSO to obtain a working concentration of 1mM and the solution was stored at -20ºC.
27. 2M Magnesium Chloride
Magnesium chloride 1.9g
ddH2O 10mL
Magnesium chloride was dissolved in ddH2O and the solution stored at room temperature. 2M magnesium chloride was diluted as required in ddH2O, and for PBS with Ca2+ and Mg2+, the diluted solution was passed through a 0.2μm filter and autoclaved prior to use.
28. 10mM MG132
MG132 4.756g
100% Ethanol 1mL
MG132 was dissolved in ethanol and the solution was stored in 100μL aliquots at -20ºC.
29. Mounting Medium
Polyvinyl alcohol (PVA)
20g
1M Tris pH7.459 50mL
1M Sodium dihydrogen orthophosphate dihydrate47
As required
Glycerol 30mL
Chlorobutanol 100mg
ddH2O 75mL
To obtain Tris-PO4 pH7.4 buffer, Tris was titrated with sodium dihydrogen orthophosphate dihydrate. 5mL Tris-PO4 pH7.4 buffer, PVA and 75mL ddH2O were combined in a conical flask, the opening of the flask was covered with parafilm and a small depression was made in the centre of the film. The flask was incubated in a 60ºC waterbath with occasional swirling overnight or until all components were dissolved, then the solution was cooled to room temperature. Glycerol was added slowly and chlorobutanol was dissolved in the solution, which was stored at 4ºC overnight to disperse air bubbles. Mounting medium was stored in airtight containers (capped 5mL or 10mL syringes) at 4ºC.
Appendix 1
268
30. Nuclear Lysis Buffer (for Subcellular Fractionation)
1M Tris pH859 50μL
0.5M EDTA18 20μL
20% SDS42 50μL
ddH2O 850μL
200mM PMSF31 5μL
40× Protease inhibitor cocktail37
25μL
Tris, EDTA, SDS and ddH2O were combined on ice in a 1.5mL tube. PMSF and protease inhibitor cocktail were added immediately before use.
31. 200mM PMSF
PMSF 348.4mg
Isopropanol 10mL
PMSF was dissolved in isopropanol in a fume hood and the solution was stored in 1mL aliquots at -20ºC.
32. Phosphate Buffered Saline (PBS)
Sodium chloride 8g
Potassium chloride 0.2g
Disodium hydrogen orthophosphate
1.44g
Potassium dihydrogen orthophosphate
0.44g
ddH2O 1L
Sodium chloride, potassium chloride, disodium hydrogen orthophosphate and potassium dihydrogen orthophosphate were dissolved in ~800mL ddH2O. The pH was adjusted to 7.2 or 7.4 using 1M sodium hydroxide or 1M hydrochloric acid, the volume was
made up to 1L with ddH2O, and the solution was autoclaved then stored at room temperature.
33. PBS with Ca2+ and Mg2+
12mM Calcium chloride6
50mL
0.01M Magnesium chloride27
50mL
PBS32 400mL
Calcium chloride and magnesium chloride were added to PBS to obtain a final concentration of 0.133g/L calcium chloride and 0.1g/L magnesium chloride. The solution was stored at room temperature.
34. PBS/1% BSA
BSA 0.05g
PBS32 5mL
BSA was dissolved in PBS and the solution was stored at 4ºC.
35. 5× PCR Buffer
Taq 10× PCR buffer (supplied with Taq DNA polymerase)
5mL
10mM dNTP16 500μL
ddH2O 4.5mL
Taq 10× PCR buffer, dNTP and ddH2O were combined and the solution was stored in 1mL aliquots at -20ºC.
Appendix 1
269
36. 300µM Phalloidin Red
Phalloidin Red 0.1mg
DMSO 255.3µL
Phalloidin Red was dissolved in DMSO and the solution was stored in 50µL aliquots at -20ºC.
37. 40× Protease Inhibitor Cocktail
Protease inhibitor cocktail tablets
4
ddH2O 1mL
Protease inhibitor cocktail tablets were dissolved in ddH2O and the solution was stored in 100µL aliquots at -20ºC.
38. 1mg/mL Rhodamine 123
Rhodamine 123 5mg
100% Ethanol 5mL
Rhodamine 123 was dissolved in ethanol and the solution was stored protected from light in 1mL aliquots at -20ºC.
39. RPMI 1640/PS
RPMI 1640 (sachet) 10.4g
Sodium hydrogen carbonate
2g
10,000U/mL Penicillin/10,000μg/mL streptomycin (PS)
10mL
ddH2O 1L
RPMI 1640 powder and sodium hydrogen carbonate were dissolved in ddH2O and the solution was sterilised using a 0.2µm filter in a laminar flow hood. RPMI 1640 and penicillin/streptomycin (PS) were combined and stored at 4ºC.
40. RPMI/5%CSS/PS
RPMI/PS39 190mL
Charcoal-treated foetal calf serum (CSS)
10mL
CSS was added to RPMI/PS and the solution was stored at 4ºC.
41. RPMI/10% (/2%) FCS/PS
RPMI/ 10%FCS
RPMI/ 2%FCS
RPMI/PS39 450mL 196mL
Foetal calf serum (FCS)
50mL 4mL
FCS was added to RPMI/PS and the solution was stored at 4ºC.
42. 20% (w/v) SDS
SDS 20g
ddH2O 100mL
SDS was dissolved in ddH2O (final volume 100mL) and the solution was stored at room temperature. During manipulation of SDS powder, protective gloves and a face mask were worn.
43. 12% Separating Gel
ddH2O 6.53mL
1M Tris pH8.859 3.75mL
40% Acrylamide (37.5:1)
4.50mL
20% SDS42 75μL
10% APS3 75μL
TEMED 7.5μL
Appendix 1
270
ddH2O, Tris, acrylamide and SDS were combined and immediately prior to use, APS and TEMED were added and the solution inverted to mix.
44. 3M Sodium Acetate pH4.6
Sodium acetate 49.2g
ddH2O 200mL
Sodium acetate was dissolved in ~160mL ddH2O, pH was adjusted to 4.6 with 1M sodium hydroxide or 1M hydrochloric acid, and the solution was autoclaved then stored at room temperature.
45. 10% (w/v) Sodium Azide
Sodium azide 0.1g
ddH2O 1mL
Sodium azide was dissolved in ddH2O and the solution was stored at 4ºC.
46. 10M Sodium Chloride
Sodium chloride 5.84mg
ddH2O 10mL
Sodium chloride was dissolved in ddH2O, the solution was autoclaved and stored at room temperature. 10M sodium chloride was diluted as required in ddH2O.
47. 1M Sodium Dihydrogen
Orthophosphate Dihydrate
Sodium dihydrogen orthophosphate dihydrate
156g
ddH2O 1L
Sodium dihydrogen orthophosphate dihydrate was dissolved in ddH2O to
a final volume of 1L and the solution autoclaved then stored at room temperature.
48. 4% Stacking Gel
ddH2O 7.70mL
1M Tris pH6.859 1.25mL
40% Acrylamide (37.5:1)
1mL
20% SDS42 50μL
10% APS3 50μL
TEMED 10μL
ddH2O, Tris, acrylamide and SDS were combined and immediately prior to use, APS and TEMED were added and the solution inverted to mix.
49. Storage Buffer (for 1kb Plus DNA Ladder™)
1M Tris pH7.559 10μL
0.5M EDTA pH818 20μL
4M Sodium chloride46 125μL
ddH2O 9.845mL
Tris, EDTA, sodium chloride and ddH2O were combined and the solution was stored at room temperature.
50. 20% (w/v) Sucrose
Sucrose 4g
ddH2O 20mL
Sucrose was dissolved in ddH2O to a final volume of 20mL and the solution was stored at room temperature.
Appendix 1
271
51. 50× TAE Buffer
Tris 242g
Glacial acetic acid 57.1mL
0.5M EDTA pH818 100mL
ddH2O 1L
Tris was dissolved in ~600mL ddH2O, the glacial acetic acid and EDTA were added, and the solution was made up to 1L with ddH2O. 50× TAE buffer was autoclaved and stored at room temperature.
52. 1× TAE Buffer
50× TAE buffer51 100mL
ddH2O 4900mL
50× TAE buffer and ddH2O were combined and the solution was stored at room temperature.
53. 1% (w/v) Toluidine Blue O
Toluidine blue O 1g
Borax 1g
ddH2O 100mL
Borax was dissolved in ~80mL ddH2O and then Toluidine Blue O was added. The solution was adjusted to 100mL and stored at room temperature. The solution was filter sterilised on the day of use.
54. Tris-Buffered Saline (TBS)
4M Sodium chloride46 18.75mL
1M Tris pH7.459 25mL
ddH2O 500mL
Sodium chloride, Tris and ddH2O were combined and the solution was stored at room temperature.
55. TBST
TBS54 500mL
Tween-20 1mL
TBS and Tween-20 were combined and the solution was stored at room temperature.
56. TBS/3% Blotto
TBS54 10mL
Skim milk powder 0.3g
Skim milk powder was dissolved in TBS and the solution constantly agitated on a horizontal shaker at room temperature. TBS/3% blotto was prepared on the day of use.
57. TBST/1% Blotto
TBST55 10mL
Skim milk powder 0.1g
Skim milk powder was dissolved in TBST and the solution constantly agitated on a horizontal shaker at room temperature. TBST/1% blotto was prepared on the day of use.
58. Transfer Buffer
Glycine 14.4g
Tris 3.03g
ddH2O 800mL
Methanol 200mL
Glycine and Tris were dissolved to a final volume of 800mL ddH2O and the solution was made up to 1L with methanol. Transfer buffer was prepared on the day of use and chilled at -20ºC prior to use.
Appendix 1
272
59. 1M Tris
Tris 121.1g
ddH2O 1L
Tris was dissolved in ~800mL ddH2O, the pH adjusted to 6.8, 7.4, 8.0 or 8.8 with 1M sodium hydroxide or 1M hydrochloric acid as required, and the solution made up to 1L with ddH2O. The solution was autoclaved, then stored at room temperature.
60. 10% (v/v) Triton-X 100
Triton-X 100 10mL
PBS32 100mL
Triton-X 100 was dissolved in PBS and the solution was stored at 4ºC.
61. 0.2% (v/v) Triton-X 100
Triton-X 100 (10% (v/v))60
200μL
PBS32 9.8mL
Triton-X 100 and PBS were combined, mixed by inversion, and the solution was stored at 4ºC.
62. 10× Western Loading Buffer
Glycerol 12.5mL
1M Tris pH6.859 2.5mL
20% SDS42 2.5mL
2-Mercaptoethanol (2-ME)
2.5g
Bromophenol blue (10mg/mL)5
0.25mL
ddH2O 25mL
Glycerol, Tris, SDS, 2-ME, bromophenol blue and ddH2O were combined in a fume hood and the
solution stored as 1mL aliquots at -20ºC.
63. 10× Western Running Buffer
Tris 60g
Glycine 288g
SDS 20g
ddH2O 2L
Tris and glycine were dissolved in ~1.8L ddH2O, SDS was added, and the volume made up to 2L with ddH2O. The solution was stored at room temperature and adjusted to 1× with ddH2O as required.
64. Whole Cell Lysis Buffer
20% Sucrose50 2.5mL
20% SDS42 0.5mL
1M Tris pH6.859 0.25mL
2-Mercaptoethanol (2-ME)
0.25mL
ddH2O 1.5mL
Sucrose, SDS, Tris, 2-ME and ddH2O were combined in a fume hood and the solution was stored protected from light in a fume hood for up to 6 weeks.
A
ppen
dix
2
APP
END
IX 2
D
ESC
RIP
TIO
N O
F G
ENES
SC
REE
NED
IN T
HE
RT2 P
RO
FILE
R E
MT
PCR
AR
RA
Y (P
AH
S-09
0Z)
G
ene
Tab
le
Sym
bol
Des
crip
tion
Gen
e N
ame
AH
NA
K
AH
NA
K N
ucle
opro
tein
A
HN
AK
RS
AK
T1
v-A
kt m
urin
e th
ymom
a vi
ral o
ncog
ene
hom
olog
ue 1
A
KT,
CW
S6, P
KB
, PK
B-A
LPH
A, P
RK
BA
, RA
C, R
AC
-ALP
HA
B
MP1
B
one
mor
phog
enet
ic p
rote
in 1
O
I13,
PC
OLC
, PC
P, P
CP2
, TLD
B
MP2
B
one
mor
phog
enet
ic p
rote
in 2
B
DA
2, B
MP2
A
BM
P7
Bon
e m
orph
ogen
etic
pro
tein
7
OP-
1 C
ALD
1 C
alde
smon
1
CD
M, H
-CA
D, H
CA
D, L
-CA
D, L
CA
D, N
AG
22
CA
MK
2N1
Cal
cium
/cal
mod
ulin
-dep
ende
nt p
rote
in k
inas
e II
inhi
bito
r 1
PRO
1489
, RP1
1-40
1M16
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Cav
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2
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V
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Cad
herin
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1 (E
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, CD
324,
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Cad
herin
2, t
ype
1 (N
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herin
) C
D32
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N, C
Dw
325,
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C
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lage
n, ty
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1 C
olla
gen,
type
III,
alph
a 1
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2 C
olla
gen,
type
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lpha
2
- C
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Bet
a-ca
teni
n
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NB
, MR
D19
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adill
o D
SC2
Des
moc
ollin
2
AR
VD
11, C
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kin
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, DPI
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Epid
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row
th fa
ctor
rece
ptor
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BB
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Erb-
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robl
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leuk
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vira
l onc
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, MD
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erb
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p180
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p45
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bB3,
p85
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bB3
ESR
1 O
estro
gen
rece
ptor
1
ER, E
SR, E
SRA
, EST
RR
, Era
, NR
3A1
F11R
F1
1 re
cept
or
CD
321,
JAM
, JA
M1,
JAM
A, J
CA
M, K
AT,
PA
M-1
FG
FBP1
Fi
brob
last
gro
wth
fact
or b
indi
ng p
rote
in 1
FG
F-B
P, F
GF-
BP1
, FG
FBP,
FG
FBP-
1, H
BP1
7 FN
1 Fi
bron
ectin
1
CIG
, ED
-B, F
INC
, FN
, FN
Z, G
FND
, GFN
D2,
LET
S, M
SF
FOX
C2
Fork
head
box
pro
tein
C2
(MFH
-1, m
esen
chym
e fo
rkhe
ad 1
) FK
HL1
4, L
D, M
FH-1
, MFH
1 FZ
D7
Friz
zled
fam
ily re
cept
or 7
Fz
E3
273
A
ppen
dix
2
GN
G11
G
uani
ne n
ucle
otid
e bi
ndin
g pr
otei
n (G
pro
tein
), ga
mm
a 11
G
NG
T11
GSC
G
oose
coid
hom
eobo
x -
GSK
3B
Gly
coge
n sy
ntha
se k
inas
e 3
beta
-
IGFB
P4
Insu
lin-li
ke g
row
th fa
ctor
bin
ding
pro
tein
4
BP-
4, H
T29-
IGFB
P, IB
P4, I
GFB
P-4
IL1R
N
Inte
rleuk
in 1
rece
ptor
ant
agon
ist
DIR
A, I
CIL
-1R
A, I
L-1R
N, I
L-1r
a, IL
-1ra
3, IL
1F3,
IL1R
A, I
RA
P,
MV
CD
4 IL
K
Inte
grin
-link
ed k
inas
e H
EL-S
-28,
ILK
-1, I
LK-2
, P59
, p59
ILK
IT
GA
5 In
tegr
in, a
lpha
5 (f
ibro
nect
in re
cept
or, a
lpha
pol
ypep
tide)
C
D49
e, F
NR
A, V
LA5A
IT
GA
V
Inte
grin
, alp
ha V
(vitr
onec
tin re
cept
or, a
lpha
pol
ypep
tide,
ant
igen
CD
51)
CD
51, M
SK8,
VN
RA
, VTN
R
ITG
B1
Inte
grin
, bet
a 1
(fib
rone
ctin
rece
ptor
, bet
a po
lype
ptid
e, a
ntig
en C
D29
in
clud
es M
DF2
, MSK
12)
CD
29, F
NR
B, G
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, MD
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, VLA
-BET
A, V
LAB
JAG
1 Ja
gged
1
AG
S, A
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, AW
S, C
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9, H
J1, J
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14
Ker
atin
14
CK
14, E
BS3
, EB
S4, K
14, N
FJ
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19
Ker
atin
19
CK
19, K
19, K
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KRT
7 K
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in 7
C
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7, K
7, S
CL
MA
P1B
M
icro
tubu
le-a
ssoc
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d pr
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n 1B
FU
TSC
H, M
AP5
M
MP2
M
atrix
met
allo
prot
eina
se 2
C
LG4,
CLG
4A, M
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A, T
BE-
1 M
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M
atrix
met
allo
prot
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se 3
C
HD
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MP-
3, S
L-1,
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TMY
1, S
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MM
P9
Mat
rix m
etal
lopr
otei
nase
9
CLG
4B, G
ELB
, MA
ND
P2, M
MP-
9 M
SN
Moe
sin
HEL
70
MST
1R
Mac
roph
age
stim
ulat
ing
1 re
cept
or (c
-met
-rela
ted
tyro
sine
kin
ase)
C
D13
6, C
Dw
136,
PTK
8, R
ON
N
OD
AL
Nod
al
HTX
5 N
OTC
H1
Not
ch 1
TA
N1,
hN
1 N
UD
T13
Nud
ix (n
ucle
osid
e di
phos
phat
e lin
ked
moi
ety
X)-t
ype
mot
if 13
-
OC
LN
Occ
ludi
n B
LCPM
G
PDG
FRB
Pl
atel
et-d
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ed g
row
th fa
ctor
rece
ptor
, bet
a po
lype
ptid
e C
D14
0B, I
BG
C4,
IMF1
, JTK
12, P
DG
FR, P
DG
FR-1
, PD
GFR
1 PL
EK2
Plec
kstri
n 2
- PP
PDE2
PP
PDE
pept
idas
e do
mai
n co
ntai
ning
2
D15
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75e,
DES
I2, D
J347
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eSI-1
, FA
M15
2B, P
PPD
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PTK
2 Pr
otei
n ty
rosi
ne k
inas
e 2
FAD
K, F
AK
, FA
K1,
FR
NK
, PPP
1R71
, p12
5FA
K, p
p125
FAK
PT
P4A
1 Pr
otei
n ty
rosi
ne p
hosp
hata
se ty
pe IV
A, m
embe
r 1
HH
72, P
RL-
1, P
RL1
, PTP
(CA
AX
1), P
TPC
AA
X1
RA
C1
Ras
-rela
ted
C3
botu
linum
toxi
n su
bstra
te 1
R
ac-1
, TC
-25,
p21
-Rac
1 R
GS2
R
egul
ator
of G
-pro
tein
sign
allin
g 2
G0S
8
274
A
ppen
dix
2
SER
PIN
E1
Serp
in p
eptid
ase
inhi
bito
r, cl
ade
E (n
exin
, pla
smin
ogen
act
ivat
or in
hibi
tor
type
1),
mem
ber 1
PA
I, PA
I-1, P
AI1
, PLA
NH
1
SIP1
Su
rviv
al o
f mot
or n
euro
n pr
otei
n in
tera
ctin
g pr
otei
n 1
SIP1
, SIP
1-de
lta
SMA
D2
SMA
D fa
mily
mem
ber 2
JV
18, J
V18
-1, M
AD
H2,
MA
DR
2, h
MA
D-2
, hSM
AD
2 SN
AI1
SN
AIL
1
SLU
GH
2, S
NA
, SN
AH
, SN
AIL
, SN
AIL
1, d
J710
H13
.1
SNA
I2
SNA
IL2/
SLU
G
SLU
G, S
LUG
H1,
SN
AIL
2, W
S2D
SN
AI3
SN
AIL
3
SMU
C, S
NA
IL3,
ZN
F293
, Zfp
293
SOX
10
SRY
(sex
det
erm
inin
g re
gion
Y)-
box
10
DO
M, P
CW
H, W
S2E,
WS4
, WS4
C SP
AR
C
Secr
eted
pro
tein
, aci
dic,
cys
tein
e-ric
h (o
steo
nect
in)
ON
SP
P1
Secr
eted
pho
spho
prot
ein
1 B
NSP
, BSP
I, ET
A-1
, OPN
ST
AT3
Si
gnal
tran
sduc
er a
nd a
ctiv
ator
of t
rans
crip
tion
3
APR
F, H
IES
STEA
P1
Six
trans
mem
bran
e ep
ithel
ial a
ntig
en o
f the
pro
stat
e 1
PRSS
24, S
TEA
P TC
F3
Tran
scrip
tion
fact
or 3
(E2A
imm
unog
lobu
lin e
nhan
cer b
indi
ng fa
ctor
s E1
2/E4
7)
E2A
, E47
, ITF
1, T
CF-
3, V
DIR
, bH
LHb2
1
TCF4
Tr
ansc
riptio
n fa
ctor
4
E2-2
, ITF
-2, I
TF2,
PTH
S, S
EF-2
, SEF
2, S
EF2-
1, S
EF2-
1A, S
EF2-
1B, S
EF2-
1D, T
CF-
4, b
HLH
b19
TFPI
2 Ti
ssue
fact
or p
athw
ay in
hibi
tor 2
PP
5, R
EF1,
TFP
I-2
TGFB
1 Tr
ansf
orm
ing
grow
th fa
ctor
, bet
a 1
CED
, DPD
1, L
AP,
TG
FB, T
GFb
eta
TGFB
2 Tr
ansf
orm
ing
grow
th fa
ctor
, bet
a 2
LDS4
, TG
F-be
ta2
TGFB
3 Tr
ansf
orm
ing
grow
th fa
ctor
, bet
a 3
AR
VD
, AR
VD
1, R
NH
F, T
GF-
beta
3 TI
MP1
Ti
ssue
inhi
bito
r of m
etal
lopr
otei
nase
1 C
LGI,
EPA
, EPO
, HC
I, TI
MP
TMEF
F1
Tran
smem
bran
e pr
otei
n w
ith E
GF-
like
and
two
folli
stat
in-li
ke d
omai
ns 1
C
9orf
2, C
T120
.1, H
7365
, TR
-1
TMEM
132A
Tr
ansm
embr
ane
prot
ein
132A
G
BP,
HSP
A5B
P1
TSPA
N13
Te
trasp
anin
13
NET
-6, N
ET6,
TM
4SF1
3 TW
IST1
Tw
ist h
omol
ogue
1
AC
S3, B
PES2
, BPE
S3, C
RS1
, SC
S, T
WIS
T, b
HLH
a38
VC
AN
V
ersi
can
CSP
G2,
ER
VR
, GH
AP,
PG
-M, W
GN
, WG
N1
VIM
V
imen
tin
CTR
CT30
, HEL
113
VPS
13A
V
acuo
lar p
rote
in so
rting
13
hom
olog
ue A
C
HA
C, C
HO
REI
N
WN
T11
Win
gles
s-ty
pe M
MTV
inte
grat
ion
site
fam
ily, m
embe
r 11
HW
NT1
1 W
NT5
A
Win
gles
s-ty
pe M
MTV
inte
grat
ion
site
fam
ily, m
embe
r 5A
hW
NT5
A
WN
T5B
Win
gles
s-ty
pe M
MTV
inte
grat
ion
site
fam
ily, m
embe
r 5B
-
ZEB
1 Zi
nc fi
nger
E-b
ox b
indi
ng h
omeo
box
1 A
REB
6, B
ZP, D
ELTA
EF1,
FEC
D6,
NIL
2A, P
PCD
3, T
CF8
,
275
A
ppen
dix
2
ZFH
EP, Z
FHX
1A
ZEB
2 Zi
nc fi
nger
E-b
ox b
indi
ng h
omeo
box
2 H
SPC
082,
SIP
-1, S
IP1,
SM
AD
IP1,
ZFH
X1B
A
CTB
B
eta-
actin
B
RW
S1, P
S1TP
5BP1
B
2M
Bet
a-2-
mic
rogl
obul
in
- G
APD
H
Gly
cera
ldeh
yde-
3-ph
osph
ate
dehy
drog
enas
e G
3PD
, GA
PD
HPR
T1
Hyp
oxan
thin
e ph
osph
orib
osyl
trans
fera
se 1
H
GPR
T, H
PRT
RPL
P0
Rib
osom
al p
rote
in, l
arge
, P0
L10E
, LP0
, P0,
PR
LP0,
RPP
0 H
GD
C
Hum
an g
enom
ic D
NA
con
tam
inat
ion
HIG
X1A
R
TC
Rev
erse
tran
scrip
tion
cont
rol
RTC
R
TC
Rev
erse
tran
scrip
tion
cont
rol
RTC
R
TC
Rev
erse
tran
scrip
tion
cont
rol
RTC
PP
C
Posi
tive
PCR
con
trol
PPC
PP
C
Posi
tive
PCR
con
trol
PPC
PP
C
Posi
tive
PCR
con
trol
PPC
276
Appendix 3
Appendix 3
278
(C)
(D)
Amplification and melt curves from analysis of the RT2 Profiler Human EMT PCR Arrays. Expression of 84 EMT-associated genes in the PCR arrays were evaluated by RT-qPCR in (A) & (B) MCF-7 and (C) & (D) T-47D cells following treatment of the cells for 24 hours with 10-8M DHT and/or 2µM cyclopamine.
A
ppen
dix
4
APP
END
IX 4
R
T2 PR
OFI
LER
EM
T PC
R A
RR
AY
FO
LD R
EGU
LATI
ON
DA
TA (M
CF-
7)
Reg
ulat
ion
(com
pari
ng to
0.1
%(v
/v) e
than
ol c
ontr
ol g
roup
) 10
-8M
DH
T 2μ
M C
yclo
pam
ine
10-8
M D
HT
+ 2
μM C
yclo
pam
ine
Fo
ld R
egul
atio
n C
omm
ents
Fo
ld R
egul
atio
n C
omm
ents
Fo
ld R
egul
atio
n C
omm
ents
AH
NA
K
1.20
58
OK
AY
-1
.045
4 O
KA
Y
1.21
76
OK
AY
A
KT1
-1
.117
3 O
KA
Y
-1.0
747
OK
AY
1.
031
OK
AY
B
MP1
1.
0792
O
KA
Y
1.02
53
OK
AY
1.
2346
O
KA
Y
BM
P2
-3.3
636
B
-1.1
439
B
-2.5
071
B
BM
P7
-1.5
801
OK
AY
1.
0042
O
KA
Y
-1.1
696
OK
AY
C
ALD
1 -1
.705
3 B
-1
.937
2 B
-6
.302
8 B
C
AM
K2N
1 -1
3682
.080
5 A
-1
.002
8 O
KA
Y
1.06
73
OK
AY
C
AV
2 1.
0353
O
KA
Y
-1.2
092
OK
AY
-1
.400
6 O
KA
Y
CD
H1
1.18
1 O
KA
Y
1.10
65
OK
AY
1.
168
OK
AY
C
DH
2 -1
.222
6 B
1.
4399
B
1.
2781
B
C
OL1
A2
1.00
7 C
-1
.016
8 C
1.
0822
C
C
OL3
A1
5.85
63
A
3.42
48
A
5.29
27
A
CO
L5A
2 1.
1487
O
KA
Y
-1.0
747
OK
AY
-1
.032
4 O
KA
Y
CTN
NB
1 -1
.328
7 O
KA
Y
-1.3
986
OK
AY
-1
.62
OK
AY
D
SC2
1.14
87
OK
AY
-1
.097
3 O
KA
Y
-1.8
1 O
KA
Y
DSP
2.
9485
O
KA
Y
2.72
45
OK
AY
2.
8759
O
KA
Y
EGFR
-1
.164
7 O
KA
Y
1.14
55
OK
AY
1.
0454
O
KA
Y
ERB
B3
1.12
51
OK
AY
1.
0253
O
KA
Y
1.07
47
OK
AY
ES
R1
-1.1
096
OK
AY
-1
.045
4 O
KA
Y
1.05
26
OK
AY
F1
1R
1.09
43
OK
AY
-1
.519
9 O
KA
Y
1.06
73
OK
AY
FG
FBP1
1.
007
C
-1.0
168
C
1.08
22
C
FN1
1.27
46
OK
AY
1.
1859
O
KA
Y
1.27
81
OK
AY
279
A
ppen
dix
4
FOX
C2
1.00
7 C
2.
307
B
3.82
11
B
FZD
7 2.
3457
O
KA
Y
2.61
35
OK
AY
1.
9507
O
KA
Y
GN
G11
1.
007
C
-1.0
168
C
1.08
22
C
GSC
-1
.094
3 O
KA
Y
-1.1
925
OK
AY
-1
.532
6 O
KA
Y
GSK
3B
1.12
51
OK
AY
1.
1219
O
KA
Y
1.19
25
OK
AY
IG
FBP4
1.
3195
O
KA
Y
1.08
37
OK
AY
-1
.011
2 O
KA
Y
IL1R
N
1.39
47
OK
AY
1.
4006
O
KA
Y
1.30
5 O
KA
Y
ILK
-1
.057
O
KA
Y
1.01
12
OK
AY
-1
.068
8 O
KA
Y
ITG
A5
-2.3
295
OK
AY
1.
325
OK
AY
-1
.822
6 O
KA
Y
ITG
AV
1.
3379
O
KA
Y
1.11
42
OK
AY
1.
226
OK
AY
IT
GB
1 1.
007
OK
AY
-1
.052
6 O
KA
Y
-1.0
614
OK
AY
JA
G1
1.26
58
OK
AY
-1
.045
4 O
KA
Y
1.06
O
KA
Y
KRT
14
1.44
39
B
-1.4
181
B
1.36
04
B
KRT
19
1.59
11
OK
AY
1.
1777
O
KA
Y
1.21
76
OK
AY
K
RT7
-1.6
702
B
-2.2
408
B
1.09
73
B
MA
P1B
2.
3784
O
KA
Y
1.25
35
OK
AY
2.
3522
O
KA
Y
MM
P2
1.00
7 C
-1
.016
8 C
1.
0822
C
M
MP3
1.
007
C
-1.0
168
C
1.08
22
C
MM
P9
2.21
91
OK
AY
2.
6684
O
KA
Y
2.83
63
OK
AY
M
SN
1.00
7 C
1.
7005
B
1.
9106
B
M
ST1R
-1
.222
6 O
KA
Y
-1.2
346
OK
AY
-1
.106
5 O
KA
Y
NO
DA
L -1
.057
B
-2
.609
9 B
-1
.169
6 B
N
OTC
H1
1.17
28
OK
AY
1.
0324
O
KA
Y
-1.1
065
OK
AY
N
UD
T13
1.44
39
OK
AY
1.
0112
O
KA
Y
1.12
82
OK
AY
O
CLN
1.
2834
O
KA
Y
1.17
77
OK
AY
1.
1204
O
KA
Y
PDG
FRB
-1
.394
7 B
-1
.428
B
-1
.297
7 B
PL
EK2
-1.2
142
OK
AY
-1
.045
4 O
KA
Y
-1.0
253
OK
AY
PP
PDE2
-1
.156
7 O
KA
Y
-1.0
31
OK
AY
-1
.018
2 O
KA
Y
PTK
2 -1
.101
9 O
KA
Y
-1.0
454
OK
AY
1.
0381
O
KA
Y
PTP4
A1
1.58
01
OK
AY
1.
4804
O
KA
Y
1.53
05
OK
AY
R
AC
1 1.
1251
O
KA
Y
1.07
62
OK
AY
1.
0747
O
KA
Y
RG
S2
-1.6
245
B
1.44
99
B
2.43
51
B
280
A
ppen
dix
4
SER
PIN
E1
1.64
72
OK
AY
1.
5115
O
KA
Y
1.26
05
OK
AY
SI
P1
-1.0
57
OK
AY
1.
0688
O
KA
Y
1.06
O
KA
Y
SMA
D2
1.07
92
OK
AY
1.
0468
O
KA
Y
-1.0
253
OK
AY
SN
AI1
-1
.181
B
-1
.016
8 B
-1
.712
4 B
SN
AI2
8.
3977
O
KA
Y
-1.0
673
OK
AY
5.
7918
O
KA
Y
SNA
I3
-1.6
702
OK
AY
-2
.240
8 O
KA
Y
-1.3
623
OK
AY
SO
X10
1.
007
C
-1.0
168
C
1.82
01
B
SPA
RC
-1
.972
5 B
1.
2799
A
-1
.262
3 B
SP
P1
-1.4
743
B
-1.5
094
B
-1.3
717
B
STA
T3
1.11
73
OK
AY
1.
0989
O
KA
Y
1.17
61
OK
AY
ST
EAP1
-1
.181
B
1.
8226
B
-1
.098
9 B
TC
F3
-1.2
834
OK
AY
1.
0042
O
KA
Y
-1.0
042
OK
AY
TC
F4
1.00
7 C
-1
.016
8 C
1.
1282
B
TF
PI2
2.47
94
OK
AY
1.
0112
O
KA
Y
2.11
99
OK
AY
TG
FB1
-1.0
792
OK
AY
1.
0112
O
KA
Y
1.08
98
OK
AY
TG
FB2
1.00
7 O
KA
Y
1.31
59
OK
AY
1.
0168
O
KA
Y
TGFB
3 -1
.189
2 O
KA
Y
-1.0
31
OK
AY
-1
.244
9 O
KA
Y
TIM
P1
1.22
26
OK
AY
1.
1696
O
KA
Y
-1.1
777
OK
AY
TM
EFF1
1.
0718
O
KA
Y
1.24
49
OK
AY
1.
2092
O
KA
Y
TMEM
132A
-1
.248
3 O
KA
Y
-1.1
127
OK
AY
1.
0098
O
KA
Y
TSPA
N13
1.
181
OK
AY
1.
0762
O
KA
Y
1.26
05
OK
AY
TW
IST1
1.
5692
B
-1
.002
8 B
2.
0056
B
V
CA
N
-1.5
911
B
-1.5
411
B
-1.4
804
B
VIM
-1
.101
9 O
KA
Y
1.15
35
OK
AY
-1
.381
3 O
KA
Y
VPS
13A
-1
.086
7 O
KA
Y
-1.0
6 O
KA
Y
1.04
54
OK
AY
W
NT1
1 1.
007
C
-1.0
168
C
1.08
22
C
WN
T5A
-1
.042
5 B
-1
.120
4 B
1.
8974
B
W
NT5
B 2.
2038
A
1.
5867
A
2.
0619
A
ZE
B1
1.09
43
B
1.14
55
B
-1.3
813
B
ZEB
2 1.
1728
O
KA
Y
-1.1
519
OK
AY
-1
.967
A
A
CTB
1.
014
OK
AY
1.
0541
O
KA
Y
1.11
27
OK
AY
B
2M
-1.0
943
OK
AY
-1
.002
8 O
KA
Y
-1.1
535
OK
AY
281
A
ppen
dix
4
GA
PDH
1.
007
OK
AY
1.
0042
O
KA
Y
-1.1
065
OK
AY
H
PRT1
-1
.042
5 O
KA
Y
-1.0
381
OK
AY
1.
1127
O
KA
Y
RPL
P0
1.11
73
OK
AY
-1
.016
8 O
KA
Y
1.03
1 O
KA
Y
HG
DC
1.
007
C
-1.0
168
C
1.08
22
C
RTC
-1
.292
4 O
KA
Y
-1.1
519
OK
AY
1.
031
OK
AY
R
TC
-1.0
497
OK
AY
-1
.082
2 O
KA
Y
1.09
73
OK
AY
R
TC
-1.0
497
OK
AY
-1
.184
3 O
KA
Y
-1.0
541
OK
AY
PP
C
1 O
KA
Y
-1.0
6 O
KA
Y
-1.0
468
OK
AY
PP
C
-1.0
792
OK
AY
-1
.097
3 O
KA
Y
-1.1
142
OK
AY
PP
C
1.02
81
OK
AY
-1
.002
8 O
KA
Y
-1.0
688
OK
AY
Com
men
ts:
A: A
vera
ge th
resh
old
cycl
e is
rela
tivel
y hi
gh (>
30) i
n ei
ther
the
cont
rol o
r the
test
sam
ple,
and
is re
ason
ably
low
in th
e ot
her s
ampl
e (<
30).
Th
ese
data
mea
n th
at g
ene
expr
essi
on is
rela
tivel
y lo
w in
one
sam
ple
and
reas
onab
ly d
etec
ted
in th
e ot
her s
ampl
e su
gges
ting
that
the
actu
al
fold
-cha
nge
valu
e is
at l
east
as la
rge
as th
e ca
lcul
ated
and
repo
rted
fold
-cha
nge
resu
lt.
This
fol
d-ch
ange
may
als
o ha
ve g
reat
er v
aria
tions
if
p-va
lue
>0.0
5; t
here
fore
, it
is i
mpo
rtant
to
have
a s
uffic
ient
num
ber
of b
iolo
gica
l re
plic
ates
to v
alid
ate
the
resu
lt fo
r thi
s gen
e.
B: A
vera
ge th
resh
old
cycl
e is
rela
tivel
y hi
gh (>
30),
mea
ning
that
its
rela
tive
expr
essi
on le
vel i
s lo
w, i
n bo
th c
ontro
l and
test
sam
ples
, and
the
p-va
lue
for t
he fo
ld-c
hang
e is
eith
er u
nava
ilabl
e or
rela
tivel
y hi
gh (p
>0.0
5).
This
fold
-cha
nge
may
als
o ha
ve g
reat
er v
aria
tions
; the
refo
re, i
t is i
mpo
rtant
to h
ave
a su
ffic
ient
num
ber o
f bio
logi
cal r
eplic
ates
to v
alid
ate
the
resu
lt fo
r thi
s gen
e.
C: A
vera
ge th
resh
old
cycl
e is
eith
er n
ot d
eter
min
ed o
r gr
eate
r th
an th
e de
fined
cut
-off
val
ue (
defa
ult 3
5), i
n bo
th s
ampl
es m
eani
ng th
at it
s ex
pres
sion
was
und
etec
ted,
mak
ing
this
fold
-cha
nge
resu
lt er
rone
ous a
nd u
n-in
terp
reta
ble.
282
A
ppen
dix
5
APP
END
IX 5
R
T2 PR
OFI
LER
EM
T PC
R A
RR
AY
FO
LD R
EGU
LATI
ON
DA
TA (T
-47D
)
Reg
ulat
ion
(com
pari
ng to
0.1
%(v
/v) e
than
ol c
ontr
ol g
roup
) 10
-8M
DH
T 2μ
M C
yclo
pam
ine
10-8
M D
HT
+ 2
μM C
yclo
pam
ine
Fo
ld R
egul
atio
n C
omm
ents
Fo
ld R
egul
atio
n C
omm
ents
Fo
ld R
egul
atio
n C
omm
ents
AH
NA
K
-1.3
775
OK
AY
-1
.802
5 O
KA
Y
-1.3
832
OK
AY
AK
T1
-1.4
359
OK
AY
-1
.602
1 O
KA
Y
-2.3
102
OK
AY
BM
P1
-1.3
031
OK
AY
-1
.547
6 O
KA
Y
-1.2
906
OK
AY
BM
P2
-1.4
763
C
-2.1
14
C
-1.3
641
C
B
MP7
-2
.332
7 A
-1
.257
O
KA
Y
-2.2
008
A
C
ALD
1 1.
4123
O
KA
Y
-1.4
142
OK
AY
1.
2243
O
KA
Y
C
AM
K2N
1 -4
.146
8 O
KA
Y
-1.1
975
OK
AY
-1
.364
1 O
KA
Y
C
AV
2 -1
.476
3 C
-2
.114
C
-1
.364
1 C
CD
H1
-1.3
398
OK
AY
-1
.484
5 O
KA
Y
-1.2
995
OK
AY
CD
H2
-2.5
527
B
-1.4
142
B
1.75
56
B
C
OL1
A2
1.39
28
B
-2.3
295
B
-1.5
032
B
C
OL3
A1
-1.4
763
C
-1.1
975
B
-1.3
641
C
C
OL5
A2
-1.7
195
OK
AY
-1
.366
O
KA
Y
-1.5
562
OK
AY
CTN
NB
1 -1
.539
O
KA
Y
-1.9
453
OK
AY
-1
.956
1 O
KA
Y
D
SC2
-1.5
933
OK
AY
-1
.624
5 O
KA
Y
-1.7
148
OK
AY
DSP
-2
.300
6 O
KA
Y
-1.5
911
OK
AY
-2
.111
1 O
KA
Y
EG
FR
1.08
52
OK
AY
-1
.375
5 O
KA
Y
1.01
54
OK
AY
ERB
B3
-1.4
763
OK
AY
-1
.515
7 O
KA
Y
-1.3
268
OK
AY
ESR
1 -1
.855
7 O
KA
Y
-1.4
641
OK
AY
-1
.492
8 O
KA
Y
F1
1R
-1.3
213
OK
AY
-1
.536
9 O
KA
Y
-1.2
728
OK
AY
FGFB
P1
-1.4
661
B
-2.4
794
B
-2.2
161
B
FN
1 -1
.672
5 O
KA
Y
-1.7
291
OK
AY
-1
.679
5 O
KA
Y
283
A
ppen
dix
5
FOX
C2
-1.4
763
C
-2.1
14
C
-1.3
641
C
FZ
D7
-1.7
925
OK
AY
-2
.114
O
KA
Y
-2.1
258
OK
AY
GN
G11
1.
0267
O
KA
Y
-1.2
746
OK
AY
1.
3122
O
KA
Y
G
SC
-1.0
585
OK
AY
-1
.301
3 O
KA
Y
-1.2
466
OK
AY
GSK
3B
-1.3
585
OK
AY
-1
.292
4 O
KA
Y
-1.3
177
OK
AY
IGFB
P4
-1.8
429
OK
AY
-1
.945
3 O
KA
Y
-1.7
63
OK
AY
IL1R
N
-2.8
324
B
1.31
95
B
-4.9
52
B
IL
K
-1.3
122
OK
AY
-1
.424
1 O
KA
Y
-1.3
547
OK
AY
ITG
A5
-5.1
766
OK
AY
-1
.790
1 O
KA
Y
-2.8
245
OK
AY
ITG
AV
1.
108
OK
AY
-1
.484
5 O
KA
Y
1.05
85
OK
AY
ITG
B1
-1.4
459
OK
AY
-1
.474
3 O
KA
Y
-1.5
032
OK
AY
JAG
1 -1
.215
9 O
KA
Y
-1.5
157
OK
AY
-1
.179
4 O
KA
Y
K
RT14
-1
.321
3 B
1.
0281
B
1.
456
B
K
RT19
2.
7664
O
KA
Y
1.80
25
OK
AY
3.
0994
O
KA
Y
K
RT7
2.06
77
OK
AY
2
OK
AY
2.
0878
O
KA
Y
M
AP1
B
-1.1
583
OK
AY
-2
.496
7 O
KA
Y
1.00
14
OK
AY
MM
P2
-1.4
763
C
-2.1
14
C
-1.3
641
C
M
MP3
-1
.476
3 C
-1
.741
1 B
-1
.364
1 C
MM
P9
-2.6
796
OK
AY
-1
.879
O
KA
Y
-2.4
083
OK
AY
MSN
-1
.476
3 C
-1
.635
8 B
1.
0295
B
MST
1R
-1.7
076
OK
AY
-1
.958
8 O
KA
Y
-1.8
378
OK
AY
NO
DA
L -1
.539
O
KA
Y
-1.4
54
OK
AY
-1
.775
2 A
NO
TCH
1 -1
.695
8 O
KA
Y
-1.4
948
OK
AY
-1
.644
9 O
KA
Y
N
UD
T13
-1.3
679
OK
AY
-1
.580
1 O
KA
Y
-1.3
177
OK
AY
OC
LN
-1.7
315
OK
AY
-2
.828
4 O
KA
Y
-1.6
223
OK
AY
PDG
FRB
-1
.476
3 C
-2
.114
C
-1
.364
1 C
PLEK
2 -2
.606
3 O
KA
Y
-1.7
777
OK
AY
-2
.510
5 O
KA
Y
PP
PDE2
-1
.241
4 O
KA
Y
-1.3
947
OK
AY
-1
.163
1 O
KA
Y
PT
K2
-1.4
969
OK
AY
-1
.494
8 O
KA
Y
-1.4
32
OK
AY
PTP4
A1
-1.2
852
OK
AY
-1
.239
7 O
KA
Y
-1.3
454
OK
AY
RA
C1
-1.2
852
OK
AY
-1
.337
9 O
KA
Y
-1.2
553
OK
AY
RG
S2
-1.0
439
B
-1.3
566
B
-1.9
159
B
284
A
ppen
dix
5
SER
PIN
E1
-8.1
794
B
-16.
2234
B
-2
.025
1 B
SIP1
-1
.312
2 O
KA
Y
-1.4
142
OK
AY
-1
.354
7 O
KA
Y
SM
AD
2 -1
.517
8 O
KA
Y
-1.4
743
OK
AY
-1
.422
1 O
KA
Y
SN
AI1
-3
.142
7 B
-1
.753
2 B
-3
.453
4 B
SNA
I2
-1.4
763
C
-2.1
14
C
-1.3
086
B
SN
AI3
-1
.426
O
KA
Y
-1.7
291
OK
AY
-1
.622
3 O
KA
Y
SO
X10
-4
.353
B
-3
.890
6 B
-1
.656
3 B
SPA
RC
-1
.111
1 B
-1
.840
4 B
-1
.691
1 B
SPP1
-1
.476
3 C
-2
.114
C
-1
.364
1 C
STA
T3
-1.1
991
OK
AY
-1
.310
4 O
KA
Y
-1.1
876
OK
AY
STEA
P1
4.71
74
OK
AY
-1
.109
6 O
KA
Y
5.39
64
OK
AY
TCF3
-1
.267
5 O
KA
Y
-1.2
226
OK
AY
-1
.364
1 O
KA
Y
TC
F4
-1.2
075
OK
AY
1.
057
OK
AY
-1
.588
9 O
KA
Y
TF
PI2
-2.9
12
B
-1.0
644
B
1.06
58
B
TG
FB1
-4.1
182
OK
AY
-2
.620
8 O
KA
Y
-3.1
34
OK
AY
TGFB
2 1.
2906
O
KA
Y
1.27
46
OK
AY
1.
0439
O
KA
Y
TG
FB3
-4.3
832
OK
AY
-1
.424
1 O
KA
Y
-1.7
387
OK
AY
TIM
P1
-2.2
222
OK
AY
-1
.853
2 O
KA
Y
-2.1
406
OK
AY
TMEF
F1
1.04
83
OK
AY
-1
.049
7 O
KA
Y
-1.1
876
OK
AY
TMEM
132A
-1
.224
3 O
KA
Y
-1.7
532
OK
AY
-1
.179
4 O
KA
Y
TS
PAN
13
-1.3
305
OK
AY
-1
.310
4 O
KA
Y
-1.2
816
OK
AY
TWIS
T1
-2.4
829
OK
AY
-1
.356
6 O
KA
Y
-1.9
972
OK
AY
VC
AN
-4
.146
8 O
KA
Y
-1.4
241
OK
AY
-2
.883
9 O
KA
Y
V
IM
-1.6
725
OK
AY
-1
.827
7 O
KA
Y
-2.0
111
OK
AY
VPS
13A
-1
.387
O
KA
Y
-1.3
947
OK
AY
-1
.336
1 O
KA
Y
W
NT1
1 -1
.339
8 B
1.
0353
B
-1
.545
4 B
WN
T5A
-1
.312
2 B
-1
.283
4 B
1.
1583
B
WN
T5B
-2.0
028
B
-1.4
743
B
1.11
11
B
ZE
B1
-1.4
763
C
1.15
67
B
1.47
63
B
ZE
B2
1.16
31
B
-3.5
064
B
1.26
75
B
A
CTB
-1
.232
9 O
KA
Y
-1.3
104
OK
AY
-1
.238
O
KA
Y
B
2M
1.07
03
OK
AY
1.
0792
O
KA
Y
1.11
11
OK
AY
285
A
ppen
dix
5
GA
PDH
2.
0534
O
KA
Y
1.89
21
OK
AY
2.
0591
O
KA
Y
H
PRT1
-1
.330
5 O
KA
Y
-1.1
096
OK
AY
-1
.462
1 O
KA
Y
R
PLP0
-1
.339
8 O
KA
Y
-1.4
044
OK
AY
-1
.264
O
KA
Y
H
GD
C
-1.4
763
C
-2.1
14
C
-1.3
641
C
R
TC
-1.5
073
OK
AY
-2
.099
4 O
KA
Y
-1.3
361
OK
AY
RTC
-1
.276
3 O
KA
Y
-1.8
15
OK
AY
-1
.187
6 O
KA
Y
R
TC
-1.3
585
OK
AY
-2
.128
7 O
KA
Y
-1.3
547
OK
AY
PPC
-1
.445
9 O
KA
Y
-2.0
705
OK
AY
-1
.432
O
KA
Y
PP
C
-1.3
967
OK
AY
-1
.931
9 O
KA
Y
-1.2
38
OK
AY
PPC
-2
.284
7 O
KA
Y
-1.9
588
OK
AY
-1
.255
3 O
KA
Y
C
omm
ents
: A
: Ave
rage
thre
shol
d cy
cle
is re
lativ
ely
high
(>30
) in
eith
er th
e co
ntro
l or t
he te
st sa
mpl
e, a
nd is
reas
onab
ly lo
w in
the
othe
r sam
ple
(<30
).
Th
ese
data
mea
n th
at g
ene
expr
essi
on is
rel
ativ
ely
low
in o
ne s
ampl
e an
d re
ason
ably
det
ecte
d in
the
othe
r sa
mpl
e su
gges
ting
that
the
actu
al
fold
-cha
nge
valu
e is
at l
east
as la
rge
as th
e ca
lcul
ated
and
repo
rted
fold
-cha
nge
resu
lt.
This
fold
-cha
nge
may
als
o ha
ve g
reat
er v
aria
tions
if p
-val
ue >
0.05
; the
refo
re, i
t is i
mpo
rtant
to h
ave
a su
ffic
ient
num
ber o
f bio
logi
cal r
eplic
ates
to
val
idat
e th
e re
sult
for t
his g
ene.
B
: Ave
rage
thre
shol
d cy
cle
is re
lativ
ely
high
(>30
), m
eani
ng th
at it
s rel
ativ
e ex
pres
sion
leve
l is l
ow, i
n bo
th c
ontro
l and
test
sam
ples
, and
the
p-va
lue
for t
he fo
ld-c
hang
e is
eith
er u
nava
ilabl
e or
rela
tivel
y hi
gh (p
>0.0
5).
This
fold
-cha
nge
may
als
o ha
ve g
reat
er v
aria
tions
; the
refo
re, i
t is
impo
rtant
to h
ave
a su
ffic
ient
num
ber o
f bio
logi
cal r
eplic
ates
to v
alid
ate
the
resu
lt fo
r thi
s gen
e.
C: A
vera
ge th
resh
old
cycl
e is
eith
er n
ot d
eter
min
ed o
r gr
eate
r th
an th
e de
fined
cut
-off
val
ue (
defa
ult 3
5), i
n bo
th s
ampl
es m
eani
ng th
at it
s ex
pres
sion
was
und
etec
ted,
mak
ing
this
fold
-cha
nge
resu
lt er
rone
ous a
nd u
n-in
terp
reta
ble.
286
A
ppen
dix
6
APP
END
IX 6
D
ESC
RIP
TIO
N O
F G
ENES
SC
REE
NED
IN T
HE
RT2 P
RO
FILE
R B
REA
ST C
AN
CER
PC
R A
RR
AY
(P
AH
S-13
1A)
Sym
bol
Des
crip
tion
Gen
e N
ame
AB
CB
1 A
TP-b
indi
ng c
asse
tte, s
ub-f
amily
B (M
DR
/TA
P), m
embe
r 1
AB
C20
, CD
243,
CLC
S, G
P170
, MD
R1,
P-G
P, P
GY
1 A
BC
G2
ATP
-bin
ding
cas
sette
, sub
-fam
ily G
(WH
ITE)
, mem
ber 2
A
BC
15, A
BC
P, B
CR
P, B
CR
P1, B
MD
P, C
D33
8, C
Dw
338,
ES
T157
481,
GO
UT1
, MRX
, MX
R, M
XR
-1, M
XR
1, U
AQ
TL1
AD
AM
23
AD
AM
met
allo
pept
idas
e do
mai
n 23
M
DC
-3, M
DC
3 A
KT1
V
-akt
mur
ine
thym
oma
vira
l onc
ogen
e ho
mol
ogue
1
AK
T, C
WS6
, PK
B, P
KB
-ALP
HA
, PR
KB
A, R
AC
, RA
C-A
LPH
A
APC
A
deno
mat
ous p
olyp
osis
col
i B
TPS2
, DP2
, DP2
.5, D
P3, G
S, P
PP1R
46
AR
A
ndro
gen
rece
ptor
A
IS, A
R8,
DH
TR, H
UM
AR
A, H
YSP
1, K
D, N
R3C
4, S
BM
A,
SMA
X1,
TFM
A
TM
Ata
xia
tela
ngie
ctas
ia m
utat
ed
AT1
, ATA
, ATC
, ATD
, ATD
C, A
TE, T
EL1,
TEL
O1
BA
D
BC
L2-a
ssoc
iate
d ag
onis
t of c
ell d
eath
B
BC
2, B
CL2
L8
BC
L2
B-c
ell C
LL/ly
mph
oma
2 B
cl-2
, PPP
1R50
B
IRC
5 B
acul
ovira
l IA
P re
peat
con
tain
ing
5 A
PI4,
EPR
-1
BR
CA
1 B
reas
t can
cer 1
, ear
ly o
nset
B
RC
AI,
BR
CC
1, B
RO
VC
A1,
FA
NC
S, IR
IS, P
NC
A4,
PPP
1R53
, PS
CP,
RN
F53
BR
CA
2 B
reas
t can
cer 2
, ear
ly o
nset
B
RC
C2,
BR
OV
CA
2, F
AC
D, F
AD
, FA
D1,
FA
NC
D, F
AN
CD
1,
GLM
3, P
NC
A2,
XR
CC
11
CC
NA
1 C
yclin
A1
CT1
46
CC
ND
1 C
yclin
D1
BC
L1, D
11S2
87E,
PR
AD
1, U
21B
31
CC
ND
2 C
yclin
D2
KIA
K00
02, M
PPH
3 C
CN
E1
Cyc
lin E
1 C
CN
E, p
CC
NE1
C
DH
1 C
adhe
rin 1
, typ
e 1,
E-c
adhe
rin (e
pith
elia
l) A
rc-1
, CD
324,
CD
HE,
EC
AD
, LC
AM
, UV
O
CD
H13
C
adhe
rin 1
3, H
-cad
herin
(hea
rt)
CD
HH
, P10
5 C
DK
2 C
yclin
-dep
ende
nt k
inas
e 2
CD
KN
2, p
33(C
DK
2)
CD
KN
1A
Cyc
lin-d
epen
dent
kin
ase
inhi
bito
r 1A
(p21
, Cip
1)
CA
P20,
CD
KN
1, C
IP1,
MD
A-6
, P21
, SD
I1, W
AF1
, p21
CIP
1 C
DK
N1C
C
yclin
-dep
ende
nt k
inas
e in
hibi
tor 1
C (p
57, K
ip2)
B
WC
R, B
WS,
KIP
2, W
BS,
p57
, p57
Kip
2
287
A
ppen
dix
6
CD
KN
2A
Cyc
lin-d
epen
dent
kin
ase
inhi
bito
r 2A
(mel
anom
a, p
16, i
nhib
its C
DK
4)
AR
F, C
DK
4I, C
DK
N2,
CM
M2,
INK
4, IN
K4A
, MLM
, MTS
-1,
MTS
1, P
14, P
14A
RF,
P16
, P16
-INK
4A, P
16IN
K4,
P16
INK
4A,
P19,
P19
AR
F, T
P16
CSF
1 C
olon
y st
imul
atin
g fa
ctor
1 (m
acro
phag
e)
CSF
-1, M
CSF
C
ST6
Cys
tatin
E/M
-
CTN
NB
1 C
aten
in (c
adhe
rin-a
ssoc
iate
d pr
otei
n), b
eta
1, 8
8kD
a C
TNN
B, M
RD
19, a
rmad
illo
CTS
D
Cat
heps
in D
C
LN10
, CPS
D, H
EL-S
-130
P EG
F Ep
ider
mal
gro
wth
fact
or
HO
MG
4, U
RG
EG
FR
Epid
erm
al g
row
th fa
ctor
rece
ptor
ER
BB
, ER
BB
1, H
ER1,
NIS
BD
2, P
IG61
, mEN
A
ERB
B2
V-e
rb-b
2 er
ythr
obla
stic
leuk
emia
vira
l onc
ogen
e ho
mol
og 2
, ne
uro/
glio
blas
tom
a de
rived
onc
ogen
e ho
mol
ogue
(avi
an)
CD
340,
HER
-2, H
ER-2
, neu
, HER
2, M
LN 1
9, N
EU, N
GL,
TK
R1
ESR
1 O
estro
gen
rece
ptor
1
ER, E
SR, E
SRA
, EST
RR
, Era
, NR
3A1
ESR
2 O
estro
gen
rece
ptor
2 (E
R b
eta)
ER
-BET
A, E
SR-B
ETA
, ESR
B, E
STR
B, E
rb, N
R3A
2 FO
XA
1 Fo
rkhe
ad b
ox A
1 H
NF3
A, T
CF3
A
GA
TA3
GA
TA b
indi
ng p
rote
in 3
H
DR
, HD
RS
GLI
1 G
LI fa
mily
zin
c fin
ger 1
G
LI
GR
B7
Gro
wth
fact
or re
cept
or-b
ound
pro
tein
7
- G
STP1
G
luta
thio
ne S
-tran
sfer
ase
pi 1
D
FN7,
FA
EES3
, GST
3, G
STP,
HEL
-S-2
2, P
I H
IC1
Hyp
erm
ethy
late
d in
can
cer 1
ZB
TB29
, ZN
F901
, hic
-1
ID1
Inhi
bito
r of D
NA
bin
ding
1, d
omin
ant n
egat
ive
helix
-loop
-hel
ix p
rote
in
ID, b
HLH
b24
IGF1
In
sulin
-like
gro
wth
fact
or 1
(som
atom
edin
C)
IGF-
I, IG
FI, M
GF
IGF1
R
Insu
lin-li
ke g
row
th fa
ctor
1 re
cept
or
CD
221,
IGFI
R, I
GFR
, JTK
13
IGFB
P3
Insu
lin-li
ke g
row
th fa
ctor
bin
ding
pro
tein
3
BP-
53, I
BP3
IL
6 In
terle
ukin
6 (i
nter
fero
n, b
eta
2)
BSF
2, H
GF,
HSF
, IFN
B2,
IL-6
JU
N
Jun
prot
o-on
coge
ne
AP-
1, A
P1, c
-Jun
K
RT18
K
erat
in 1
8 C
K-1
8, C
YK
18, K
18
KRT
19
Ker
atin
19
CK
19, K
19, K
1CS
KRT
5 K
erat
in 5
C
K5,
DD
D, D
DD
1, E
BS2
, K5,
KRT
5A
KRT
8 K
erat
in 8
C
AR
D2,
CK
-8, C
K8,
CY
K8,
K2C
8, K
8, K
O
MA
PK1
Mito
gen-
activ
ated
pro
tein
kin
ase
1 ER
K, E
RK
-2, E
RK
2, E
RT1,
MA
PK2,
P42
MA
PK, P
RKM
1,
PRK
M2,
p38
, p40
, p41
, p41
map
k, p
42-M
APK
M
APK
3 M
itoge
n-ac
tivat
ed p
rote
in k
inas
e 3
ERK
-1, E
RK
1, E
RT2
, HS4
4KD
AP,
HU
MK
ER1A
, P44
ERK
1,
288
A
ppen
dix
6
P44M
APK
, PR
KM
3, p
44-E
RK
1, p
44-M
APK
M
APK
8 M
itoge
n-ac
tivat
ed p
rote
in k
inas
e 8
JNK
, JN
K-4
6, JN
K1,
JNK
1A2,
JNK
21B
1, 2
, PRK
M8,
SA
PK1,
SA
PK1c
M
GM
T O
-6-m
ethy
lgua
nine
-DN
A m
ethy
ltran
sfer
ase
- M
KI6
7 A
ntig
en id
entif
ied
by m
onoc
lona
l ant
ibod
y K
i-67
KIA
, MIB
-, M
IB-1
, PPP
1R10
5 M
LH1
Mut
L ho
mol
og 1
, col
on c
ance
r, no
npol
ypos
is ty
pe 2
(E. c
oli)
CO
CA
2, F
CC
2, H
NPC
C, H
NPC
C2,
hM
LH1
MM
P2
Mat
rix m
etal
lope
ptid
ase
2 (g
elat
inas
e A
, 72k
Da
gela
tinas
e, 7
2kD
a ty
pe IV
co
llage
nase
) C
LG4,
CLG
4A, M
MP-
2, M
MP-
II, M
ON
A, T
BE-
1
MM
P9
Mat
rix m
etal
lope
ptid
ase
9 (g
elat
inas
e B
, 92k
Da
gela
tinas
e, 9
2kD
a ty
pe IV
co
llage
nase
) C
LG4B
, GEL
B, M
AN
DP2
, MM
P-9
MU
C1
Muc
in 1
, cel
l sur
face
ass
ocia
ted
AD
MC
KD
, AD
MC
KD
1, C
A 1
5-3,
CD
227,
EM
A, H
23A
G, K
L-6,
M
AM
6, M
CD
, MCK
D, M
CK
D1,
MU
C-1
, MU
C-1
, SEC
, MU
C-1
, X
, MU
C1,
ZD
, PEM
, PEM
T, P
UM
M
YC
V
-myc
mye
locy
tom
atos
is v
iral o
ncog
ene
hom
olog
(avi
an)
MR
TL, M
YC
C, b
HLH
e39,
c-M
yc
NM
E1
Non
-met
asta
tic c
ells
1, p
rote
in (N
M23
A) e
xpre
ssed
in
AW
D, G
AA
D, N
B, N
BS,
ND
KA
, ND
PK-A
, ND
PKA
, NM
23,
NM
23-H
1 N
OTC
H1
Not
ch 1
A
OS5
, AO
VD
1, T
AN
1, h
N1
NR
3C1
Nuc
lear
rece
ptor
subf
amily
3, g
roup
C, m
embe
r 1 (g
luco
corti
coid
rece
ptor
) G
CC
R, G
CR
, GC
RST
, GR
, GR
L PG
R
Prog
este
rone
rece
ptor
N
R3C
3, P
R
PLA
U
Plas
min
ogen
act
ivat
or, u
roki
nase
A
TF, B
DPL
T5, Q
PD, U
PA, U
RK
, u-P
A
PRD
M2
PR d
omai
n co
ntai
ning
2, w
ith Z
NF
dom
ain
HU
MH
OX
Y1,
KM
T8, M
TB-Z
F, R
IZ, R
IZ1,
RIZ
2 PT
EN
Phos
phat
ase
and
tens
in h
omol
ogue
10
q23d
el, B
ZS, C
WS1
, DEC
, GLM
2, M
HA
M, M
MA
C1,
PTE
N1,
TE
P1
PTG
S2
Pros
tagl
andi
n-en
dope
roxi
de sy
ntha
se 2
(pro
stag
land
in G
/H sy
ntha
se a
nd
cycl
ooxy
gena
se)
CO
X-2
, CO
X2,
GR
IPG
HS,
PG
G, H
S, P
GH
S-2,
PH
S-2,
hC
ox-2
PYC
AR
D
PYD
and
CA
RD
dom
ain
cont
aini
ng
ASC
, CA
RD
5, T
MS,
TM
S-1,
TM
S1
RA
RB
R
etin
oic
acid
rece
ptor
, bet
a H
AP,
MC
OPS
12, N
R1B
2, R
RB
2 R
ASS
F1
Ras
ass
ocia
tion
(Ral
GD
S/A
F-6)
dom
ain
fam
ily m
embe
r 1
123F
2, N
OR
E2A
, RA
SSF1
A, R
DA
32, R
EH3P
21
RB
1 R
etin
obla
stom
a 1
OSR
C, P
PP1R
130,
RB
, p10
5-R
b, p
Rb,
pp1
10
SER
PIN
E1
Serp
in p
eptid
ase
inhi
bito
r, cl
ade
E (n
exin
, pla
smin
ogen
act
ivat
or in
hibi
tor
type
1),
mem
ber 1
PA
I, PA
I-1, P
AI1
, PLA
NH
1
SFN
St
ratif
in
YW
HA
S
289
A
ppen
dix
6
SFR
P1
Secr
eted
friz
zled
-rela
ted
prot
ein
1 FR
P, F
RP-
1, F
RP1
, Frz
A, S
AR
P2
SLC
39A
6 So
lute
car
rier f
amily
39
(zin
c tra
nspo
rter)
, mem
ber 6
LI
V-1
, ZIP
6 SL
IT2
Slit
hom
olog
2 (D
roso
phila
) SL
IL3,
Slit
-2
SNA
I2
Snai
l hom
olog
2 (D
roso
phila
) SL
UG
, SLU
GH
1, S
NA
IL2,
WS2
D
SRC
V
-src
sarc
oma
(Sch
mid
t-Rup
pin
A-2
) vira
l onc
ogen
e ho
mol
ogue
(avi
an)
ASV
, SR
C1,
c-S
RC
, p60
-Src
TF
F3
Tref
oil f
acto
r 3 (i
ntes
tinal
) IT
F, P
1B, T
FI
TGFB
1 Tr
ansf
orm
ing
grow
th fa
ctor
, bet
a 1
CED
, DPD
1, L
AP,
TG
FB, T
GFb
eta
THB
S1
Thro
mbo
spon
din
1 TH
BS,
TH
BS-
1, T
SP, T
SP-1
, TSP
1 TP
53
Tum
our p
rote
in p
53
BC
C7,
LFS
1, P
53, T
RP5
3 TP
73
Tum
our p
rote
in p
73
P73
TWIS
T1
Twis
t hom
olog
ue 1
(Dro
soph
ila)
AC
S3, B
PES2
, BPE
S3, C
RS,
CR
S1, C
SO, S
CS,
TW
IST,
bH
LHa3
8 V
EGFA
V
ascu
lar e
ndot
helia
l gro
wth
fact
or A
M
VC
D1,
VEG
F, V
PF
XB
P1
X-b
ox b
indi
ng p
rote
in 1
TR
EB-5
, TR
EB5,
XB
P-1,
XB
P2
B2M
B
eta-
2-m
icro
glob
ulin
-
HPR
T1
Hyp
oxan
thin
e ph
osph
orib
osyl
trans
fera
se 1
H
GPR
T, H
PRT
RPL
13A
R
ibos
omal
pro
tein
L13
a L1
3A, T
STA
1 G
APD
H
Gly
cera
ldeh
yde-
3-ph
osph
ate
dehy
drog
enas
e G
3PD
, GA
PD, H
EL-S
-162
eP
AC
TB
Act
in, b
eta
BR
WS1
, PS1
TP5B
P1
HG
DC
H
uman
Gen
omic
DN
A C
onta
min
atio
n H
IGX
1A
RTC
R
ever
se T
rans
crip
tion
Con
trol
RTC
R
TC
Rev
erse
Tra
nscr
iptio
n C
ontro
l R
TC
RTC
R
ever
se T
rans
crip
tion
Con
trol
RTC
PP
C
Posi
tive
PCR
Con
trol
PPC
PP
C
Posi
tive
PCR
Con
trol
PPC
PP
C
Posi
tive
PCR
Con
trol
PPC
Gen
e T
able
290
Recommended